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Top Python Data Science Courses & Tutorials for Mastery

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July 02, 2023 · min read

As a well-known programming language, Python dominates the data science field. Its prominence in the industry represents the main reason why so many job offers include Python skills as a hard requirement.

Of course, all of the hype around Python has practical ramifications. This programming language is suitable for people without a programming background. If you have a sufficient grasp of technology, chances are you’ll get how Python works in a few weeks.

Besides being beginner-friendly, Python is practically built for math and statistical analysis. Plus, data visualization becomes nearly effortless when you use specific Python libraries dedicated to the task.

The point is that Python makes numerous data science tasks and operations easier. If you’re interested in data science, learning this versatile programming language will take your professional development to a new level.

Fortunately, you can find plenty of courses teaching everything from the basics to advanced functions in Python. Let’s look at the best Python data science tutorial and course options.

Factors to Consider When Choosing a Python Data Science Course

Before you start a particular course, it would be best to consider the specifics. The criteria that should guide your decision include:

The content of the course: Some courses will be introductory, while others will offer advanced lessons. You should start with a course that aligns with your proficiency level.
Instructor’s expertise: Ideally, you’ll want an industry expert to teach you about Python. Experienced lecturers or proven professionals will know all of the ins and outs, and they’ll be able to transfer that knowledge to you.
Course duration and flexibility: If you’re looking for a course, you don’t want an experience that will last an entire year. On the other hand, you shouldn’t expect too much from an hour-long course. Additionally, the course structure should be flexible enough to allow you to complete it at your own pace.
Practical projects and applications: Python is a living programming language that sees plenty of use in the real world. On that note, the course you take should offer a hands-on experience and show you how to apply your new knowledge in practice.
Course reviews and ratings: Although this shouldn’t be your primary clue when making a decision, taking a look at what others say about the course certainly won’t hurt. You’ll want to stay away from courses with mostly negative reviews, especially if the reviewers make unsubstantiated claims.
Pricing and value: Course pricing may vary from ludicrously expensive to free. While our list doesn’t include any outrageously overpriced courses, you’ll find a quality free one in there. The bottom line here is straightforward: Does the course fit in with your budget and what do you get for the price?

Additional Resources for Mastering Python Data Science

If you want an alternative to an actual Python data science course, you may wish to turn to other resources that will help you master the subject. In particular, these would be books and digital resources like forums, eBooks, podcasts, YouTube channels, websites, and blogs.

For some of the best Python forums and online communities, check out the following:

Python org forums
StackOverflow Python forum page
FreeCodeCamp Python category

Great books on Python include:

Head-First Python, by Paul Barry
Think Python, by Allen B. Downey
Learn Python 3 the Hard Way, by Zed A. Shaw
Python Crash Course, by Eric Matthes

If printed media isn’t your style, you can find an excellent list of free Python eBooks on Codeburst.io.

On the other hand, you might not want to read too much while learning Python. In that case, you’ll be glad to learn that there are numerous podcasts on the subject that you can tune in to right now:

Unsurprisingly, YouTube also has plenty of Python data science course and tutorial channels. Here are our top picks:

The New Boston
Sentdex
Real Python
PyCon – This isn’t a particular YouTube channel, but rather a search query. Browse the search results on YouTube, and you’ll find videos for Python-dedicated conferences from around the world.
Michael Kennedy

Finally, there’s an abundance of blogs and websites dedicated to Python resources and knowledge:

Learn to Program in Python Like a Pro

The internet is full of quality Python data science tutorial and course pages. You can find free and premium resources to hone your skills in the programming language or get familiar with the fundamental concepts.

Whichever resource type you choose, rest assured that learning practical Python skills will be a valuable addition to your resume. After all, data science is a constantly developing field in which expanding your knowledge base and skillset can only be a huge plus. If you’ve found a program you like in this article, don’t hesitate to jump right into it and expand your horizons.

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Top Data Science Tutorial Options for Beginners and Experts

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OPIT - Open Institute of Technology

July 02, 2023 · min read

Imagine that you own a business that has thousands of customers. You have data on every one of these customers, ranging from basic contact information to data about their purchasing habits. What you have is a huge dataset, and you want to extract information from that dataset in the form of patterns and insights with which you can make decisions.

You’d need a data scientist.

Data scientists specialize in shining a spotlight on the most important insights found in large datasets. They use a range of tools – from complex algorithms to artificial intelligence – to make that spotlight shine brighter. And in a world of Big Data, the data scientist’s role is more important now than ever. With these six courses, split between beginner, intermediate, and advanced levels, you put yourself in a prime position to become the data scientist that so many companies need.

Best Data Science Tutorials for Beginners

Everybody has to start somewhere, and these data science beginner tutorial options are the ideal first step on your journey into the field.

Data Science Tutorial for Beginners (Java T Point)

If you’re looking for a succinct explanation of what data science is, what it involves, and how it applies in the modern world, Java T Point’s tutorial answers the key questions. It’s structured as a long-form article rather than a set of modules or lessons, but it’s well-organized and covers all of the key points in enough depth to make it a handy primer for the data science novice.

This data science tutorial covers a range of topics, from basic explanations of the components of data science to descriptions of the types of jobs available for those who enter the field. It also digs into some of the machine learning aspects of data science, such as decision trees, so you can see how AI ties into modern data science practices.

Granted, the fact that it’s not a traditional course means there’s no community underpinning the tutorial or certification for completion. But as a primer that gives you some foundational knowledge, it’s a superb starting point.

Data Science Full Course – Learn Data Science in 10 Hours (Edureka)

Offered via YouTube, this data science tutorial makes the lofty claim of being able to teach you all you need to know about the subject in 10 hours. While that isn’t strictly true (the more complex aspects are covered superficially), it’s still a great primer for those looking to build a solid foundation in the subject.

The tutorial is a great choice for visual learners, and it covers topics like data categorization, statistics, and the data lifecycle. Charts, graphs, and other visual learning tools abound, with the constant narration helping you to understand what you’re seeing on screen.

As a full 10-hour video, the tutorial could do with being broken up into separate lessons to make it easier to keep your place. But as long as you’re happy to record time stamps (or don’t mind the full 10 hours in one sitting), the course delivers plenty of useful information.

Best Data Science Tutorials for Intermediate Learners

After completing a few of the best data science tutorials for beginners, you’re ready to get your feet wet with intermediate courses that dig into the coding that underpins data science.

Data Science with Python Tutorial (Geeksforgeeks)

Python is the programming language of choice for data scientists, as evidenced by the fact that 69% of data scientists report using Python daily. It’s no surprise, either, as Python is an extremely flexible language that’s ideal for creating the algorithms needed in data science due to its vast range of libraries. The challenge you face is twofold – figuring out how to code in Python and understanding what libraries you need to confront common data science challenges.

Geeksforgeeks offers a data science tutorial that confronts both of those challenges and helps you see how Python applies to the data science field in a practical sense. Starting with a brief introduction to the data science field (the beginner-level tutorials in this list offer more depth), it then dives into everything you need to know about Python. You’ll learn about the basics of Python, such as functions and control statements, before moving into how you can use the language for visualizing data and creating machine learning models.

It’s a highly specialized tutorial, though it’s one that’s essential for prospective data scientists, given the popularity of Python in the field. Unfortunately, there’s no certification for completion. However, it’ll equip you with so much Python knowledge that you can feel confident moving into a more advanced study without worrying about your coding chops.

Data Science and Machine Learning Essentials (Microsoft via Udemy)

Like the above course, Microsoft’s offering covers Python, albeit in far less depth. However, it stands out because it also covers a couple of other languages used commonly in data science – namely R and Azure Machine Learning. As a result, the course is an excellent choice for intermediate data scientists who want to get to grips with the main three programming languages they’ll likely use in the field.

It’s a five-week course, with Microsoft recommending between three and four hours of learning per week, and it’s delivered in English. Each weekly module is capped with a quiz that tests your knowledge. The modules cover everything from data science basics to creating machine learning models in Azure Machine Learning.

Of course, the biggest benefit of this course (aside from the content) is the Microsoft-approved certification you get at the end. Any employer who sees Microsoft on your CV will sit up and take notice. Still, you’ll need to build on what you learn here with a more advanced data science tutorial, ideally one that covers more real-world applications of working with data.

Best Data Science Tutorials for Advanced Learners

Once you’re secure in your foundational knowledge and you have a good idea of how to apply data science practices, you’re ready to step into a more advanced data science tutorial. Here are two options.

Data Science Tutorial – Learn Data Science From Scratch (DataFlair)

Think of DataFlair’s main data science tutorial page as a hub world in a video game. There are dozens of different directions in which to take your studying, and you’re in complete control of where you go and what you learn. The page hosts over 370 tutorials (free of charge) that cover everything from the basics of data science to using data mining and Python to parse through massive data sets.

The sheer depth of coverage makes this set of tutorials ideal for the advanced learner. The more basic sides of the course can fill in any knowledge gaps that weren’t covered in previous tutorials you’ve taken. And on the more advanced side, you’ll be exposed to real-world examples that show you how to apply your theoretical knowledge in a practical environment. There’s even a set of quizzes that you can use to test your understanding of what you read.

There are some drawbacks, namely that this data science tutorial doesn’t offer a certificate and is less interactive than many paid courses. However, self-paced learners who thrive when presented with pages of theoretical knowledge will find almost everything they need to know about data science in this collection.

MicroMasters® Program in Statistics and Data Science (Massachusetts Institute of Technology)

By the time you’re at the advanced stage of learning data science, you’ll probably want an official certification to take pride of place on your CV. This mini-Master’s degree comes from the Massachusetts Institute of Technology (MIT), which is one of the world’s leading technology and engineering schools.

The course lasts for one year and two months, with between 10 and 14 hours of study required per week, making it a choice only for those who can commit to a part-time consistent learning schedule. It’s also not a free data science tutorial, as you’ll have to pay £1,210 (approx. €1,401) for the program.

If you can vault those hurdles, you get a graduate-level course that teaches you how to develop the machine learning models used in modern data science. Plus, having the letters “MIT” on your course certification (and the networking opportunities that come with learning from some of the institutions leading professors) makes this course even more valuable.

Find the Best Data Science Tutorials for Your Skill Level

Whether you’re taking your first tentative steps into the world of data science or you’re an advanced learner looking to brush up your skills, there’s a data science tutorial out there for you. The six highlighted in this article represent the best data science tutorials available (two for each skill level) on the web.

Let’s close by answering a key question – why complete one of these tutorials?

Precedence Research has the answer, stating that the data science field will enjoy a compound annual growth rate (CAGR) of 16.43% between 2022 and 2030. Rapid growth means more job opportunities (and higher salaries) for those with data science skills. Use these tutorials to build your skill base before shifting your career focus to a field that looks set to explode as Big Data becomes more crucial to how companies operate.

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Artificial Intelligence and Data Science Courses: The Top Picks

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OPIT - Open Institute of Technology

July 02, 2023 · min read

For decades, we have used computers to make important decisions in every arena, from business down to our personal lives. Artificial intelligence is the next evolution in computer-based decision-making. Combined with data science, which is the art of processing, extracting, and analyzing data, AI stands to hold a huge influence over our future.

You stand at the cusp of that technological wave. By completing an artificial intelligence and data science course, you develop dual capabilities that put you in the perfect position to enjoy a superb career.

Factors to Consider When Choosing an AI and Data Science Course

You need to know what you’re letting yourself in for before choosing a data science and artificial intelligence course. After all, the course you choose (and its quality) will impact your career prospects. Consider these six factors when making your choice.

1 – Course Content

Both data science and AI are expansive fields that contain a lot of categories and specializations. So, the question you need to ask is does the course cover what I need to know to get the job I want? If it doesn’t, you end up dedicating months (or even years) of your life to a course that brings you no closer to your goals.

2 – Course Duration and Flexibility

Not every student has the luxury of being able to commit full-time to an AI and data science course. Some have work, families, and other commitments to maintain. Ideally, your course should be of an appropriate length for your needs, in addition to offering the flexibility you need to fit your studies around the rest of your life.

3 – Instructor Expertise and Experience

Though data science has been around for decades, AI is still a somewhat nascent field, at least in terms of its modern form. You want to see that your course is created and overseen by people who know what they’re talking about. Do they have direct industry experience? Are their qualifications up to standard? What does your instructor have that makes taking their AI and data science course worthwhile?

4 – Course Fees and Return on Investment

A career in data science is usually strong enough to offer a good return on investment, with European data scientists pulling in an average of €60,815 per year. Throw AI into the mix and you have extra skills that could easily lead you toward six figures. Still, the cost of the course plays a role in your decision, with some courses costing five figures themselves.

5 – Online vs. Offline Courses

Picking between online and offline courses is like playing an arcade game with a guaranteed prize – there’s no way to lose. Your only consideration is what works best for you. Offline courses are great for self-motivated learners who need flexibility. Online courses put you in a classroom environment so you have direct contact with instructors and peers.

6 – Certification and Accreditation

When you finally start applying for jobs, the first thing your potential employer will ask is “Where did this person study their artificial intelligence and data science course?” The answer to that question will impact their decision, meaning your course provider needs to have a solid enough reputation to make their certifications and accreditations worth having.

Top AI and Data Science Courses

There is a metaphorical river of courses, both online and off, that can teach you about artificial intelligence and data science. Here are four of the best.

Course 1 – AI For Business Specialization (University of Pennsylvania via Coursera)

AI, Big Data, and the core concepts behind machine learning combine to create this AI and data science course. Beyond teaching you how to apply these computing concepts in a business setting, AI For Business Specialization digs into the ethics of applying AI fairly inside a business and how these evolving technologies will affect the people you work with, for, and manage.

Key Features

Direct exposure to industry-hardened professionals who apply the skills you’re learning
Includes peer-reviewed assessments designed to test your knowledge
A 100% online course that offers complete flexibility in how you schedule your learning
No experience in data science or AI required to get started

Pros and Cons

For somebody new to the concepts of AI and data science, this is the perfect course because it starts you out at the beginner level and builds you up from there. It’s flexible, too, with the course providers recommending two hours of learning per week to complete the four-month course. However, the course carries no university credit, so those using it to supplement their existing studies have to make do with the certificate and nothing more.

Course 2 – Machine Learning (Udacity)

Those looking for a budget-conscious artificial intelligence and data science course can rely on Udacity to provide its Machine Learning course at no charge. You’ll need a solid understanding of concepts like linear algebra and probability theory, making this course unsuitable for beginners. But assuming you come prepared, you’ll learn about the main approaches in machine learning (supervised, unsupervised, and reinforcement learning) in a self-paced online environment.

Key Features

Takes approximately four months to complete, though you can finish at your own pace
Created and taught by industry experts
Ideal for building foundational knowledge for future courses related to data science and AI
Teaches multiple approaches to machine learning

Pros and Cons

The price is certainly right with this course, as you’re getting something very useful at no cost. It’s also an online version of class CS7641, which is taught at Georgia Tech, so the course has real-world credentials behind it. Sadly, its college-based origins don’t mean that you’ll get college credit with the course. It’s also pretty limited to specific forms of machine learning, making it great as an introduction to basic concepts but perhaps not as useful to people who already have some understanding of data science and AI.

Course 3 – Introduction to Artificial Intelligence (AI) (IBM via Coursera)

Quick, intense, and practical are just some of the words we can use to describe this data science and artificial intelligence course. IBM’s experts are clearly masters in the field (they wouldn’t be working for IBM if they weren’t) and they’ve distilled some of the best of their knowledge into this nine-hour completely online course. You’ll learn about the applications of AI in real-world scenarios, start getting to grips with concepts like machine learning and neural networks, and receive direct career advice from your instructors.

Key Features

Offered by a Fortune 50 company that specializes in AI and data science
Free enrollment for a self-paced course
You get direct career advice from people who work in the field
The course offers a shareable online certificate that looks great on your LinkedIn profile

Pros and Cons

Let’s get the obvious out of the way first – this is an AI and data science course for those who want to learn the fundamentals before building their knowledge in other ways. But it’s the connections that come with the course that make this such a strong contender. Having people from IBM, who already work in the field that interests you, to advise you is great for people who need a route into AI and data science.

Course 4 – Master in Applied Data Science & AI (OPIT)

A Master’s degree allows you to dig deeper into the concepts of AI and data science, with OPIT’s degree being perfect for those in the postgraduate phase who’ve balked at the cost of similar programs. This AI and data science course requires an extensive time investment of between 12 and 18 months, though it’s fully online so you can learn at your own pace. It also counts toward college credits, offering 90 ECTS upon completion.

Key Features

Completely online so it offers flexibility in terms of how and where you learn
Provided by an EU-accredited institution to ensure the certification you receive is actually useful
You get 24/7 access to tutors who can advise you when you’re stuck
Progressive assessments are favored over “final exams” and other high-pressure tests

Pros and Cons

This artificial intelligence and data science course is the most expensive on the list, clocking in at €6,500 (or €4,950 for early birds). It also requires a BSc in an appropriate field, such as computer science, to start studying. But that investment in both time and money leads you to a course that has full accreditation under the European Qualification Framework and gives you a well-rounded set of skills that set you up for C-Suite positions in your future career.

Tips for Success in AI and Data Science Courses

An AI and data science course could offer the best tutelage in the world but it won’t mean a thing if you’re not applying yourself as a student. These quick tips help you take what you learn further:

Set clear goals for what you hope to achieve, both within the course and after completion, so you always have a path to follow.
Don’t take “this course requires x number of hours per week” as given. Practice and set time to study whenever you can to build on your knowledge.
As valuable as your peers and instructors may be, they’re not the only resources available to you. Engage with online communities and forums to stay up to date on trends in AI and data science.
Some courses offer direct examples of how what you learn applies to the real world. Others don’t, so you have to seek out (and apply) your learning to real projects yourself.
Think about what AI looked like five years ago compared to today. This is a continuously evolving field (the same goes for data science), so continued learning is a must once you’ve completed your course.

Combine AI and Data Sciences for Career Advancement

Earlier, we stated that data scientists earn an average of €60,815 per year in Europe. That’s a starting point. Mastery in the fields of AI and data science (which starts with an artificial intelligence and data science course) puts you in a position to work at the C-Suite level in many of today’s businesses. Investing in yourself now, when these fields are still in their growth phase, puts you in the perfect position to take advantage as we see both fields enjoy explosive growth in the future.

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Artificial Intelligence Free Course Online With Certificate

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OPIT - Open Institute of Technology

July 02, 2023 · min read

AI is everywhere today.

The algorithms that drive your Netflix and Spotify recommendations use AI to figure out what you’ll like based on what you’ve already consumed. Every chatbot you’ve ever spoken to, targeted ad you’ve seen, and even the more fanciful ideas floating around (self-driving cars, anyone?) use AI to some degree.

Given that so many businesses use AI already, it stands to reason that taking online courses on the subject will help you get ahead. But for the budget-conscious among you, a course that costs thousands of euros isn’t the route you want to go down. You want a free AI course.

That’s where this article comes in. But let’s get something clear immediately, a free AI course won’t go into as much depth as a paid one. Nor will it give you a qualification that’s as prestigious as one from a formal educational institution. But what it will give you is foundational knowledge, often backed by a certification, which is why we’re looking at four of the best AI courses you can study for free in this article.

Top Artificial Intelligence Course Online Free With Certificate – Four Great Options

Is it really possible to find an artificial intelligence free course with certificate that shows you have actually learned something useful? It is, and these four courses are great examples.

Course 1 – Elements of AI (University of Helsinki)

With over 950,000 students already to its name, the Elements of AI course is all about lifting the veil on the mysterious concept of AI. It includes two modules, the first giving you an introduction to the “whats” and “wherefores” of AI, with the second digging into building your own AI models. It’s set up to run in 170 countries and is ideal for those who want a basic grasp on AI that they can build on with other courses.

Key Topics Covered

The theory of AI, including what is and isn’t possible with the tech
Development of basic AI algorithms
An introduction (and exploration) of using Python to create AI models
Practical exercises that you can take at your own pace to see how AI applies in real-world scenarios

Certificate Details

The certification you get from this free AI course comes directly from the University of Helsinki, which is a recognized and authoritative European institution. But it’s important to note that the certificate is not a degree. Instead, it’s both a demonstration of your grasp of basic AI concepts and a statement of your intent to dig deeper into the topic.

Course 2 – Machine Learning With Python: A Practical Introduction (IBM)

There are three things you want from your AI course – online, free, and practical. IBM’s offering delivers all three, with the focus being on how you can apply machine learning (with Python programs underpinning your models) to the real world. The content is created and delivered by Saeed Aghabozorgi, who’s a senior data scientist at IBM, meaning it comes direct from somebody who understands precisely how machine learning is applied in practical terms.

Key Topics Covered

Python programming in the context of creating machine learning models
The theory and application of both supervised and unsupervised learning
An introduction to the most common machine learning algorithms
Real-world examples of how machine learning is already impacting society

Certificate Details

In return for five weeks of your time (estimated study – four to five hours per week) you’ll earn an IBM “skill badge.” This online credential verifies that you’ve completed the course and can be shared on social media profiles. The course is also part of IBM’s Data Science Professional Certificate Program, making it a piece of a larger jigsaw puzzle of free AI courses that you can complete over the course of a year to get an IBM certificate.

Course 3 – Supervised Machine Learning: Regression and Classification (DeepLearning.AI via Coursera)

You’re getting into specialization territory with this course, which serves as the first of several that make up DeepLearning.AI’s Machine Learning Specialization certificate. It’s a completely online course that allows you to reset deadlines to suit your schedule and takes about 33 hours of studying to complete. Sadly, it’s only available in English (at the time of writing), which may make it less accessible to non-English speakers.

Key Topics Covered

A wide-spanning introduction to the various types of machine learning
Explanations of the best practices for AI implementation currently used in major Silicon Valley companies
Several mathematical and statistical concepts, such as linear regression
Practical examples and project work for building predictive machine learning models

Certificate Details

Coursera provides its own shareable certificates to anybody who completes this course, with those certificates being shareable on social media and printable for your CV. It’s also worth noting that this course is part of a wider three-course program. Combine it with DeepLearning.AI’s Advanced Learning Algorithms and Unsupervised Learning and Recommender Systems to get two more course-specific certificates and a certificate for completing all three courses.

Course 4 – Learn With Google AI (Google)

Learn with Google AI is less a dedicated course and more a collection of different modules (and even competitions) designed to help you get to grips with AI. Think of it like a resource bank, only it incorporates practical exercises as well as theoretical information. Beyond the courses themselves, you’ll find a useful glossary and some guides for how AI can apply to environmental and social courses.

Key Topics Covered

Theoretical modules covering machine learning, neural networks, and the ethics behind AI
Hands-on tutorials that give you practical experience with the course content
Real-world examples of how Google incorporates AI into what it does
Competitions that allow you to test your skills against other participants

Certificate Details

Learn with Google AI isn’t a traditionally structured course, and that’s reflected in the lack of certification for completing the courses in this resource bank. It’s better to think of these courses as free primers that equip you with the knowledge you need to ace other free (or paid) AI courses.

Factors to Consider When Choosing an AI Course

The price is certainly right with a free AI course, but you’re still investing valuable time into whichever program you choose. Think about the following to ensure you spend that time wisely:

Course content – Though many artificial intelligence free course will cover the basic concepts underpinning AI, you want to know that you’re going somewhere with what you learn. Think about why you’re studying AI and whether the course will move you closer to your goals.
Course duration and flexibility – Online courses come with a key advantage over traditional programs – you control your studying. That flexibility allows you to fit your studies around your life, though you still have deliverables (and sometimes tests) you need to complete.
Instructor credentials – With free courses, the certification you get isn’t as immediately prestigious as one you’d receive from a paid course. A respected instructor can add that prestige. Research the background of whoever creates and delivers the course, specifically checking their reputation as a teacher and experiences in the AI industry.
Community support and resources – Given that most free AI courses focus on self-learning, you need to know that there are people (or resources) around to help when you get stuck. No learner is an island. If there are other students and instructors around to offer guidance, you have a course that you’re more likely to pass.
Certificate value – As touched upon earlier, the value of your certificate plays a role in your decision, with specific attention being paid to how employers will see that certificate on your CV. A respected instructor or a course delivered by a major brand (think Google or IBM) adds credibility compared to courses delivered by nameless and faceless individuals.

Tips for Successfully Completing an AI Course Online

No athlete gets a gold medal for running half a race, and the same applies to students who don’t complete the courses they start. Use these tips to see you through when the going gets tough:

Set clear goals for yourself, which inform the course you choose and help to motivate you if you start feeling discouraged when struggling with the material.
Dedicate time to learning both in the context of your course and by parsing out personal time for practice.
Engage with the community that’s evolved around the course to learn directly from peers and qualified professionals.
Never be afraid of seeking help when needed, as you’re learning some complex concepts that are all too easy to misinterpret.
Take every opportunity you can find to apply the theoretical concepts you learn in real-world scenarios.

Study AI Courses Free Online

A free AI course is never going to be a direct substitute for a paid course delivered by a recognized institution. But it doesn’t have to be. Free courses can set you up with general skills that you can apply in your existing workplace, in addition to helping you lay a foundation for future study. And in some cases (such as with courses offered directly by major AI players) you’ll get a certification that actually means something to employers.

AI is going to be so much more than a part of future technology. It’ll be the bedrock on which everything to come is built. Your efforts to expand your knowledge in the field will help you become one of the people who lay that bedrock. The sooner you start learning (and applying) AI, the better your position will be when the AI revolution truly takes hold.

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Artificial Intelligence Tutorial: The Top Guides for AI Mastery

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OPIT - Open Institute of Technology

July 02, 2023 · min read

Artificial intelligence (AI) is a modern-day monolith that is likely going to be as important to the world as the introduction of the internet. We already see it creeping into every aspect of industry, from the basic chatbots you find on many websites to the self-driving cars under production at companies like Tesla.

As an industry, AI looks set to zoom past its current global valuation of $100 billion, becoming worth a staggering $2 trillion by 2030. To ensure you enjoy a prosperous career in an increasingly computer-powered world, you need to learn about AI. That’s where each artificial intelligence tutorial in this list can help you.

Additional AI Resources

The six tutorials in this list run the gamut from introducing you to the basics of AI to demonstrating specialized applications of the technology. Building on that knowledge requires you to go further, with the following books, podcasts, and websites all being great resources.

Great AI-Related Books

Artificial Intelligence: A Modern Approach (Peter Norvig and Stuart Russell)
Python: Advanced Guide to Artificial Intelligence (Giuseppe Bonaccorso)
Neural Networks and Deep Learning (Charu C Aggarwal)

Great AI-Related Podcasts

The AI Podcast (Noah Kravitz)
Artificial Intelligence: AI Podcast (Lex Fridman)
Eye on AI (Craig Smith)

Great AI-Related Websites and Blogs

MIT News
Analytics Vidhya
KDnuggets

Understand Complex Concepts With an Artificial Intelligence Tutorial

AI is one of the world’s fastest-growing industries, with the previously-mentioned $2 trillion 2030 valuation representing a 20-fold growth from today. The point? Getting in close to the ground floor now by developing your understanding of AI concepts will set you up for a future in which many of the best jobs are in the AI field.

Each artificial intelligence tutorial in this list offers something different to students, from beginners who want to get to grips with AI to those who have a decent understanding and are ready to specialize. Regardless of the course you choose, the most important thing is that you keep learning. AI won’t stay static. It’s like a runaway locomotive that’s going to keep plowing forward, with nothing to stop it, to its next evolution. Use these tutorials to learn both basic and advanced concepts, then build on that learning with continued education.

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Data Science Online Course: Master, Certify & Learn the Best

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OPIT - Open Institute of Technology

July 02, 2023 · min read

Digital technologies pretty much run the modern world. From our phones and computers to manufacturing, finance, and retail, so many aspects of life rely on machines crunching unimaginable quantities of data.

As a discipline at the core of this digital era, data science is still expanding its scope. Leading organizations in this sector never seem to get enough of new talent, and the demand for data science specialists is constantly rising.

Luckily, the same digital-first environment that depends on data science also gives ample opportunities for learning this essential trade. You can easily find a data science course online, and the same goes for certifications. Better yet, there are Masters programs you can take without leaving your home.

If the prospect of online data science courses sounds exciting, this article will recommend some of the best available programs.

Top Data Science Online Courses

There’s no shortage of options to learn data science online. The courses that made our list come from prestigious institutions and offer the most comprehensive approach to the subject.

When choosing the top courses, we followed straightforward criteria. We looked into institution reputation, hands-on experiences, lecture quality, and comprehensiveness. Here are the best online data science courses that excelled in these categories.

Metis – Data Science & Analytics Training

If you’re looking for an online course with live lectures, then Data Science & Analytics Training from Metis will be a great choice. The lecturers come from leading tech companies, giving lessons that cover the complete data science process.

While there are advanced bootcamps on offer, Metis provides a comprehensive beginner data science online course with certificate, which lasts for six weeks. The price for this course is $750 (roughly 695 euros at time of writing). This course offers an accredited certificate.

Dataquest – Introduction to Python Programming

Dataquest is somewhat unique as it represents a knowledge repository for standalone learning or as a supplementary resource. If you want to learn data science with this platform, the Introduction to Python Programming course is a quality choice.

The class is brief, informative, and suited for beginners. It consists of six lessons and a practical project, with an estimated 12 hours needed to complete the self-paced course. While the introductory course doesn’t offer certification, it will open up a learning path with Dataquest that does end up in winning an expert-reviewed credential.

A third of the learning resources is available for free. The full access to Dataquest courses will require a subscription to the service with a monthly or yearly model.

Harvard University – CS109 Data Science

Getting education from Harvard is about as elite as one can get. The CS109 Data Science course embodies all the benefits of learning from a prestigious institution like Harvard. The course teaches data science essentials, including Python programming, statistics, and machine learning. The complete material is accessible on dedicated GitHub pages. You can clone the repository to get access to the entire curriculum.

Since this is just the repository of resources, going through them won’t give you a certificate. However, it’s free and completely available online, making it an educational opportunity you shouldn’t miss. With the detailed knowledge of the basics under your belt, you’ll progress to more complex (and pricier) courses with ease.

Online Data Science Master’s Programs

You might think that getting a master’s diploma requires you to physically attend a college. And while that used to be the case only a few decades ago, you can enroll in a master’s program online. Better yet, you may do so at a reputable institution with a world-leading data science department.

We picked several top-tier online data science masters programs online. Our choice was based on similar criteria as for the courses:

How reputable is the institution?
Does the program offer practical knowledge?
Are the lectures comprehensive and quality-made?

With all that in mind, here are our top choices of online master’s programs in data science.

University of Aberdeen – Data Science MSc

The University of Aberdeen is one of the leading educational institutions in the UK. The Data Science MSc program is the university’s regular MSc data science online program that’s also completely available online. The curriculum includes vital skills concerning algorithms, data analysis, mathematical modeling, and more.

With full-time learning, the degree can be completed in one year. However, you can study at your own pace and take as much time as you need between individual courses. The limit for completion is six years, and enrolling in the program will cost £14,920.

Rome Business School – International Online Master in Data Science

The International Online Master in Data Science from the Rome Business School represents an excellent opportunity to learn, get in touch with industry-leading companies, and build a professional network. The school houses bootcamps across Europe and worldwide, which may increase your job market reach.

The participation fee for this program is €6,700. If paid after starting the course, applicants can split the cost into six installments, free of interest. Covering the fee in installments in advance will grant you a 5% discount. Paying in a lump sum comes with a 10% discount.

European Leadership University – Professional Master in Data Science & Leadership

The European Leadership University offers a comprehensive program that includes individual and group work, as well as interactive workshops. Completing the Professional Master in Data Science & Leadership program will earn you a master’s degree and two recognized certificates: in data science and leadership.

The program is priced at €5,000, with the option to pay the fee in five installments during the study period. Upfront payments come with a 10% discount. The program includes classes on machine learning, statistics, data collection and handling, Python programming, and more. This master’s course lasts for 19 months.

Key Skills to Learn in Data Science

Data science consists of numerous fields, some of which are more theoretical while other lean heavily towards practical applications. The later data science aspects include essential skills that you can use in the market:

Programming languages
Data visualization and reporting
Machine learning and AI
Big data
Statistics

In programming, languages like Python, R, and SQL are used to create program environments and write specific commands. As a data science skill, the study of programming languages explores the limitations and possibilities of existing and new languages.

Data visualization deals with representing complex datasets in a more comprehensive way. It’s related to reporting and may be viewed as its subset. Visualization tools include charts, graphs, and presentations.

Machine learning might be the most well-known aspect of data science. Technologies like deep learning are at the core of AI development, enabling machines to learn from limited data input. Recently, great advances were made in unsupervised learning, which doesn’t require human input at all.

Big data refers to processing and analyzing large amounts of information. Handling massive data volumes presents specific challenges in terms of computational capacity and error reduction.

Finally, statistics form one of the cornerstones of practical data science use. Statistical analysis is helpful in business, demographics, and numerous social and natural sciences. Reliable statistics help researchers create predictive models and projections, allowing for efficient planning down the line.

Benefits of Earning a Data Science Certificate or Degree

Getting a degree or certificate in data science offers you an edge both in professional improvement and in the job market. The very process of gaining credentials is an opportunity to learn and practice essential skills. Plus, you can build a respectful portfolio along the way.

A degree or certificate means better job opportunities. Every reputable employer in the field will want to see recognized credentials from their applicants, and that’s particularly true when hiring for better-paid positions.

If you’ve already got a starting-level job in data science, credentials from reputable institutions will help advance your career. That kind of growth also creates a potential for better salaries and work benefits.

Finally, once you enroll in a data science degree or certificate program, you’ll meet other people pursuing similar interests. This will be an excellent opportunity for networking. Combined with the credentials, your new network of colleagues can help you advance even further.

Tips for Choosing the Right Data Science Online Course or Program

When you start searching for the right program online, it’s vital to consider several factors:

The content and curriculum of the course
Instructor expertise and reputation in the industry
The duration of the program
How flexible the course is
Pricing and whether there are options for financial aid
Testimonials or reviews from previous students

Besides these considerations, you should account for your personal preferences. Define your goals and what you want to achieve with the program. Also, it’s important for the program to match the learning style that suits you the best.

Gain the Essential Skills for the Hottest Profession Today

Our data science course suggestions include a selection of programs from the most respected industry leaders. With the high-quality courses on offer, all you’ll need to do is pick the program that matches your career goals.

Today’s job market has a high demand for data science experts. Getting certified or earning a degree in the field will help you start a career easier, which is why you should consider this important move as soon as possible.

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Machine Learning Tutorial: Top Online Resources for Machine Learning Mastery

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OPIT - Open Institute of Technology

July 01, 2023 · min read

It can often feel like a computer has a “brain,” especially given modern machines’ abilities to run complex calculations and handle instructions. But all of those machines need people behind them to program algorithms and help them to learn based on explicit instructions. That’s where machine learning comes in.

This branch of artificial intelligence brings a machine’s “brain” closer to the real thing than ever before. It’s all about teaching the machine how to do more than simply execute, as machine learning is all about making a machine “think” (based on instructions and algorithms) so it can improve over time. That ability to “think” is crucial in modern business because it gives companies the ability to analyze patterns – both operational and consumer-based – enabling them to make smarter decisions.

But these businesses need people who understand how to create machine learning models. That’s where you come in. With the right machine learning tutorial under your belt, you set yourself up for a career in a field that has only just started to show glimpses of its potential.

The Best Machine Learning Tutorials

Finding the best online tutorial for machine learning isn’t easy given the sheer volume of options available. Analyzing each one based on what it teaches (and how useful it will be to your career) takes time, though you can save yourself that time by checking out the three tutorials highlighted here.

Tutorial 1 – Intro to Machine Learning (Kaggle)

As tempting as it may be to run before you can walk, you need an introduction to the basic concepts of machine learning prior to focusing on more practical applications. Enter Kaggle’s machine learning tutorial. This seven-lesson course takes about three hours of self-guided learning to complete and will leave you with a solid grounding in machine learning that you can take into more industry-focused courses.

The majority of the seven lessons – barring the first – is split into two parts. First comes a tutorial where you’ll learn about the concepts that the lesson introduces, with the second part being an exercise that tests your new skills. Along the way, you’ll learn the basics of how machine learning models work and why you need them to explore large datasets. Other lessons focus on building and validating a model, with the later lessons introducing more complex algorithms, such as random forests, and giving you a chance to test your skills in competitions.

Though this is a beginner-focused tutorial, you’ll need a solid understanding of Python before making a start. Without experience in this programming language, you’ll feel like you’re truly lost in a random forest before you ever get to learn what that term actually means. On the plus side, the tutorial has an active discussion community (which includes the course instructor Dan Becker) that can help you along and point you in the direction of other courses that supplement this one.

Tutorial 2 – Making Developers Awesome at Machine Learning (Machine Learning Mastery)

This machine learning tutorial is less a structured course and more a series of articles and step-by-step instructional lessons that take you from the foundations of machine learning to more advanced concepts. That method of breaking the course into multiple stages is ideal for students of all experience levels. Complete beginners can start with the “Foundations” level and work their way up while those with more experience can dip into specific subjects that give them trouble or will build on their existing skills.

The course is split into four sections – Foundations, Beginner, Intermediate, and Advanced. At the Foundations level, you’ll learn about the statistical concepts and models that underpin machine learning, giving you a solid basis to move into the Python programming taught in the Beginner section. Once you have a grasp of Python, the Intermediate section teaches you about deep learning and how to code machine learning algorithms. By the time you hit the Advanced stage, you’ll be working on complex subjects like computer vision and natural language processing.

With its less structured nature, this tutorial is great for people who want to dip in and out and those who need to hone in on a specific aspect of machine learning. It’s also a good choice for beginners because it covers practically everything you’ll need to know. Unfortunately, the lack of structure means you don’t get an official certification from the tutorial. Some students may also not like the “hub” nature of the tutorial, as it links you to tons of different web pages that can lead to confusion over time.

Tutorial 3 – Machine Learning Crash Course With TensorFlow APIs (Google)

If you already have a mathematical foundation (as well as some basic understanding of machine learning), Google’s tutorial helps you take your skills to the next level. You’ll need to understand algebra, statistics, and basic trigonometry, in addition to having some understanding of Python, to get started. But assuming you have all of that, this machine learning tutorial exposes you to real-world examples of the technology in action.

It’s a 25-lesson course that contains 30 exercises covering topics like model development and testing, data representation, and building neural networks. According to Google, it takes about 15 hours of self-guided study to complete, though your time may vary depending on how much you already know before you start the course.

The biggest advantage of this tutorial is the name attached to it. Google is a major player in the tech industry and the presence of its name on your CV instantly shows employers that you know your stuff. The course material is also delivered by lecturers who work at or for Google, allowing them to bring their real-world experiences into their lessons. On the downside, the tutorial’s prerequisites make it unsuitable for beginners, though Google does offer more basic courses (both in machine learning and Python) to help you build the required foundation.

Factors to Consider When Choosing a Machine Learning Tutorial

The three options presented above all make a solid case for the best online tutorial for machine learning, though each offers something different based on your current skill level. To make the best choice between the three (and any other tutorials you find) you should consider these factors before committing yourself.

Your Current Skill Level

Diving into neural networks before you even know how machine learning works is like trying to row upstream without a paddle. You’re going to get stuck in rough waters and the end result won’t be what you want it to be. Be honest with yourself about your current skill level to ensure you don’t start a tutorial that’s too difficult (or too simple) for your abilities.

Programming Languages

There’s no getting away from the fact that you’ll need to feel comfortable with programming before taking a machine learning tutorial. Specifically, you’re likely to need some knowledge of Python, though how much depends on the course you take. Other languages can help, at least in the sense of ensuring you’re familiar with programming, but you need to check the language the course uses before starting.

Specific Topics

Though the basic idea of building a machine “brain” is simple enough to understand, the machine learning waters run deep. There are tons of topics and potential specializations you could study, and not all are useful for your intended career path. Check what the course covers and ensure those topics align with what you hope to achieve once you’ve completed the tutorial.

Time Commitment

If a tutorial takes an hour or two to complete, you don’t really need to worry about how you’ll fit it around your other commitments. But if it takes you down a machine learning rabbit hole (i.e., the Machine Learning Mastery Course), you need to get serious with scheduling. Figure out how much time you can commit to your course per week and choose a tutorial that fits around your commitments.

The Cost

On the plus side, many machine learning tutorials are available free of charge. But if you’re looking for more official certification, or you want to take a more formal course, you’ll usually have to pay for the privilege. Weigh up the course’s cost against the benefit you get out of the backend.

Tips for Getting the Most Out of a Machine Learning Tutorial

Anybody can start a machine learning tutorial, but only the truly committed will complete and actually get the most out of the materials. Follow these tips to ensure you’re spending your time wisely on the tutorial you choose:

Set clear goals from the outset that define what you want to achieve with the tutorial and where it’s supposed to lead you.
Dedicate time to learning every week because regularity is the key to making the information you absorb stick in your mind.
Engage with any communities related to your tutorial to learn from your peers and ask questions about the tutorial’s content.
Apply what you learn to real-world problems, either via the course itself or by searching for examples of what you’ve learned being put into action.
Update your knowledge and skills regularly with further tutorials because what you learn today may be out of date tomorrow.

Find the Best Online Tutorial for Machine Learning for You

There is no single “best” machine learning tutorial on the web because each approaches the subject differently. Some assume you have no knowledge at all and will start with basics before moving you into deeper subjects. Others require you to understand the computing concepts (mathematical and programmatical) that underpin machine learning before you can get started. Understand what the course offers, and what it needs from you, before you get started.

Regardless of your choice, getting started is the most important thing you can do. Once you’ve chosen a tutorial, commit yourself to it fully to take your first step (or potentially a giant leap) into a career that’s only going to grow as machine learning models become more common in business.

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Data Science Certification: The Top 10 Online Courses & Programs

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OPIT - Open Institute of Technology

July 01, 2023 · min read

Data science is likely the most sought-after profession today. With top tech organizations looking for talent across the world, this field is highly competitive. That’s why professional improvement represents a crucial aspect of this rapidly-evolving industry.

Getting an approved certificate is the best way to gain the necessary knowledge and a confirmation of your data science skills. This article will give you a list of the 10 best online courses and data science certificate programs that offer worldwide recognized certification.

Factors to Consider When Choosing a Data Science Certification Course

There’s plenty of criteria to look at when choosing a data science certification course online. Of course, the content of the course will be of most interest, especially since data science is a broad field. But several other aspects are also worth researching:

Program duration
Flexibility – is it on a fixed timeline or self-paced
Instructor quality and the reputation of the institution
Pricing
Whether the program offers practical projects and hands-on work
Whether the institution will help you land your next job

Top 10 Online Data Science Certification Courses & Programs

Here’s a brief overview of what the top online courses in data science have to offer. Courses and programs on our list come from respected institutions that hire world-class lecturers and will provide the best certification for data science you could get without setting foot on campus.

Harvard University – Professional Certificate in Data Science

Getting an education in data science from Harvard University is one of the best options in the market. This online course teaches essential skills in programming, modeling, statistics, data visualization, and numerous data science tools.

The Professional Certificate in Data Science course is self-paced and represents an introductory course tailored for beginners who want to advance their skills. You’ll also learn through relevant case studies by analyzing data from real-life examples. The program includes working in the R environment.

The price of this Harvard program is $991, with an available 10% discount. The course runs through the edX platform, and allows you free access to the entire curriculum at your leisure. If you decide for the minimal 2-3 hour weekly commitment, the certificate will take roughly 17 months to complete.

Cloudera – Data Platform Generalist Certification

The Data Platform Generalist test by Cloudera is excellent because it enables learners to take various roles within the data science industry. While the exam focuses on Cloudera’s data platform, the program certifies you as a general data science professional, meaning you can pursue a career in data engineering and analytics, development, administration, and similar fields.

The certification consists of a single 90-minute exam with 60 questions. Cloudera doesn’t state the minimal score needed to pass the exam because the point of the certification program is to do it the best you can rather than aiming for a specific score.

According to the Cloudera website, this certification costs $330. Upon completing the exam, you’ll get a certificate that lasts for two years.

IBM – Data Science Professional Certificate

As one of the industry leaders, IBM provides an exceptional course in data science. The course teaches the basics of data science, focusing on the work methodology via Python and SQL. The Data Science Professional Certificate program helps beginners in the field via hands-on work, with exercises in data set importing, analysis, cleaning, and visualization.

The online certificate course in data science consists of 10 parts. After the first three introductory courses, the following six focus on working in Python, while the final one deals with applied data science. This is a flexible, self-paced program suitable for beginners.

Enrolling in this IBM data science program is free via Coursera, provided you have a monthly subscription. The courses require about three hours of work per week. At that tempo, you should complete the program and receive your data science certification within five months.

Data Science Council of America – Senior Data Scientist

As the name implies, the Data Science Council of America (DASCA) counts among the leading authorities on data science in the U.S. and worldwide. The Senior Data Scientist program enjoys global recognition and takes place entirely online.

This program provides excellent resources that candidates can use to prepare for the exams. Plus, the resources are quality reading for the purposes of professional improvement. The learning material and the program itself are suitable for more experienced learners.

Upon enlisting, you’ll need to cover a one-time fee of $775. Once you receive the resources, you’ll have six months to prepare for the exam. The recommended study time is up to 10 hours weekly.

John Hopkins University – Data Science Specialization

When a reputable institution like the John Hopkins University offers a specialization in data science, there’s no reason to miss that opportunity. Hosted by Coursera, this Data Science Specialization course is built around practical applications of actual data.

The online program provides learners the chance to create a genuine data product. Along with learning, you’ll also be building a respectable portfolio that will come in handy as a demonstration of your newly acquired skills.

Like other Coursera programs, this specialization is also free with a subscription to the service. The program is flexible in terms of time commitment. If you devote an hour a day to it, you can complete the specialization in about 11 months.

Microsoft – Azure AI Fundamentals

Microsoft has proven to be not only a tech giant but an excellent knowledge hub. With Azure AI Fundamentals, this renowned company offers expertly crafted training in the basics of working with artificial intelligence. Through this certification program, learners can gain a thorough understanding of AI and become skilled in the latest technologies.

This online data science certificate course will be suitable even for complete beginners, although a basic level of programming skills would give you an easier start. The program comes in two variants: self-paced and led by a professional instructor.

The program costs only €99 and awards a permanent Microsoft certificate. You can also try out the course with a trial subscription, and there’s an available practice assessment test that will help you understand where you stand before enrolling.

MIT – MicroMasters Program in Statistics and Data Science

If you’re looking for an intensive program that will teach you advanced data science skills, MIT has just the thing. The MicroMasters in Statistics and Data Science is a result of a collaboration between the world-renowned MIT and edX, a trusted learning platform.

This program includes working on data sets from real-world examples, as well as understanding the leading machine learning models. Upon finishing, candidates will be eligible for different titles within the field of data science.

The program consists of five courses and may last up to 14 months with about 14 hours of weekly engagement. The edX platform lists the program price at $1,350.

Open Group – Certified Data Scientist

The Open Group consists of numerous global organizations, with some of the most distinct members being technology giants like IBM, Intel, Fujitsu, and Huawei. The Certified Data Scientist certification that the group provides is a credential recognizes around the globe.

The structure of this program is quite unique. It doesn’t include courses or exams. Instead, applicants need to demonstrate practical data science skills in written form. The point of this certification isn’t to educate, but rather to verify the candidate’s professional capabilities.

The time needed to get the certificate will vary depending on your proficiency level. The certificate is permanent, and Open Group discloses its price via contact.

Stanford University – Machine Learning Certification

Stanford University is home to some of the world’s finest lecturers. The institution provides a machine learning program in collaboration with Coursera and, as a practical, hands-on experience, it’s something eager learners shouldn’t miss.

The Machine Learning Certification is an ideal opportunity for beginners to grasp the intricacies of advanced AI and its applications. The program consists of three courses. By the end of the third course, the applicant should be able to build Python machine learning models from the ground up.

Following Coursera’s standard model, this program is free to enroll into, provided the user has a Coursera subscription. With up to nine hours of work weekly, the program shouldn’t last more than three months.

SAS – Certified AI and Machine Learning Professional

SAS is a certification program that operates globally. It offers a Certified AI and Machine Learning Professional program that’s built for people looking for top practical education in these areas. As the name says, this certification is aimed at future data science professionals.

The program includes five courses after which attendees get permanent certification. Upon registering, learners will receive a full year of access to the complete course material, as well as 70 hours of complimentary software use via cloud.

This program is self-paced, but you have to complete it within one year. The price for one year is €1,295.

Tips for Success in Data Science Certification Courses

Enrolling in a data science course is only a part of the process. To be successful, you’ll need to do your best and employ certain techniques:

Manage your time effectively. Make sure to commit enough time to progress through the course and meet requested deadlines.
Start building a network with your peers from day one. Collaborate with people who share your interest in data science so that you can build off of each other.
Never assume you’ve learned everything there is to know. Data science is evolving constantly, and there’s always new skills to develop and additional knowledge to gain.
Build a strong portfolio that will increase your chances of finding a job in the field. The best data science certification programs represent an ideal start.

Get Certified in One of the Top Professions Today

Getting a data science certificate online can open up a career path in a top-paid profession that continues to grow. With certification from one of the leading institutions in the field, you’ll be on the right track to success.

Our list contains programs and courses from renowned organizations like Harvard, IBM, MIT, and Microsoft. The quality of lecturers is unquestionable, and the programs offer the most up-to-date courses. Whichever certification you choose, you can rest assured you’ll be the best data science certification online.

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MSc in Applied Data Science & AI

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Factors to Consider When Choosing a Python Data Science Course

Top Python Data Science Courses and Tutorials

ILX Group – Python E-Learning

Key Topics

Instructor’s Background

Course Duration and Format

Pricing and Enrollment

Pros

Cons

Python Institute – Data Analysis Essentials With Python

Key Topics

Instructor’s Background

Course Duration and Format

Pricing and Enrollment

Pros

Cons

Python-Course – Fundamental Python Course

Key Topics

Instructor’s Background

Course Duration and Format

Pricing and Enrollment

Pros

Cons

Additional Resources for Mastering Python Data Science

Learn to Program in Python Like a Pro

Best Data Science Tutorials for Beginners

Data Science Tutorial for Beginners (Java T Point)

Data Science Full Course – Learn Data Science in 10 Hours (Edureka)

Best Data Science Tutorials for Intermediate Learners

Data Science with Python Tutorial (Geeksforgeeks)

Data Science and Machine Learning Essentials (Microsoft via Udemy)

Best Data Science Tutorials for Advanced Learners

Data Science Tutorial – Learn Data Science From Scratch (DataFlair)

MicroMasters® Program in Statistics and Data Science (Massachusetts Institute of Technology)

Find the Best Data Science Tutorials for Your Skill Level

Factors to Consider When Choosing an AI and Data Science Course

1 – Course Content

2 – Course Duration and Flexibility

3 – Instructor Expertise and Experience

4 – Course Fees and Return on Investment

5 – Online vs. Offline Courses

6 – Certification and Accreditation

Top AI and Data Science Courses

Course 1 – AI For Business Specialization (University of Pennsylvania via Coursera)

Key Features

Pros and Cons

Course 2 – Machine Learning (Udacity)

Key Features

Pros and Cons

Course 3 – Introduction to Artificial Intelligence (AI) (IBM via Coursera)

Key Features

Pros and Cons

Course 4 – Master in Applied Data Science & AI (OPIT)

Key Features

Pros and Cons

Tips for Success in AI and Data Science Courses

Combine AI and Data Sciences for Career Advancement

Top Artificial Intelligence Course Online Free With Certificate – Four Great Options

Course 1 – Elements of AI (University of Helsinki)

Key Topics Covered

Certificate Details

Course 2 – Machine Learning With Python: A Practical Introduction (IBM)

Key Topics Covered

Certificate Details

Course 3 – Supervised Machine Learning: Regression and Classification (DeepLearning.AI via Coursera)

Key Topics Covered