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?

Top Python Data Science Courses and Tutorials

ILX Group – Python E-Learning

This Python data science course deals with the basic functionality of the programming language and teaches you how to apply it in practice. It contains in-depth information about command running, dictionaries, methods, and shell scripting. No final exam is necessary to complete the course.

Key Topics

  • The basics of Python programming
  • File and data operations
  • Logging and test infrastructure
  • Conditional statements
  • Networking
  • Shell scripting
  • Django web framework

Instructor’s Background

Information about the instructor for this course isn’t available on ILX Group.

Course Duration and Format

The course is in e-learning format and is delivered entirely online. It will take you about eight hours to complete. Instead of a final exam, you’ll complete the course by submitting the required project that must meet specific set criteria.

Pricing and Enrollment

Enrolling in this course will cost €450 +VAT. You won’t need to fulfill any additional requirements to make a start. Paying the one-time fee will grant you a full year of access to the course resources.

Pros

  • Provides a solid foundation for Python programming
  • No limitations on enrollment or availability
  • Offers practical knowledge and projects

Cons

  • E-learning tools used throughout the course aren’t defined
  • No information about the instructor or their credentials

Python Institute – Data Analysis Essentials With Python

The Python Institute is a group devoted to Python education. The Data Analysis Essentials with Python is only one of the courses this institution provides. It’s an intermediate-level program focused on data analysis using the tools within the Python programming language.

Key Topics

  • Data analysis
  • Algorithmic and analytical thinking
  • Data visualization
  • Statistics
  • Data mining and modeling
  • Programming
  • Data-based decision-making

Instructor’s Background

No instructor information can be found on the Python Institute site regarding this particular course. However, it’s worth mentioning that the institute is run by industry experts with substantial experience in the IT sector. These experts are also responsible for the institute courses.

Course Duration and Format

The Data Analysis Essentials with Python course will last for up to six weeks, provided you devote about eight hours weekly to studying the material. The course is delivered online.

Pricing and Enrollment

One of the greatest advantages of this course is its pricing: Data Analysis Essentials with Python is completely free. However, this course isn’t for beginners. You’ll need previous knowledge of the key concepts in Python programming. The Python Institute recommends completing their beginner courses or coming into this program with some experience.

Pros

  • Course designed by industry professionals
  • Free for all users
  • May serve as a preparatory course for Python Certified Associate in Data Analytics (PCAD) certification

Cons

  • No information about the lecturer
  • Exact delivery methods aren’t specified

Python-Course – Fundamental Python Course

The Fundamental Python Course is designed as a comprehensive introduction to programming methods in Python. The course will take you through the fundamentals of the programming language and include practical solutions in the Python environment.

Key Topics

  • Python introductory lessons
  • Script editing and execution
  • Working in the Python shell
  • Expressions, operators, assignments, and variables
  • Dictionaries, stacks, loops, and lists
  • Handling files and exceptions
  • Conditional statements
  • Packages and modules

Instructor’s Background

The instructor for live courses is Bernd Klein. A Python expert with a Saarland University diploma in Computer Science, specializing in computer languages, Klein has taught at the Saarland University, EWH, Koblenz, and the University of Freiburg, where he still holds a teaching position.

Klein is also the founder of the programming language teaching platform, Bodenseo.

Course Duration and Format

The course lasts for five days and includes a live class format. While Klein usually holds classes in person, courses are currently provided online. To participate on this course, you’ll need a network-ready computer with a microphone. No additional software is needed.

Pricing and Enrollment

The on-site variant of the course costs €1,450 per day, while open classes start from €349 daily. There are no other requirements for the course.

Pros

  • Taught by an experienced lecturer
  • Offers a complete coverage of Python-related subjects
  • Advanced optional topics

Cons

  • Very pricey compared to the competitors
  • Doesn’t provide a certificate

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:

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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Juggling Work and Study: Interview With OPIT Student Karina
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jun 5, 2025 6 min read

During the Open Institute of Technology’s (OPIT’s) 2025 Graduation Day, we conducted interviews with many recent graduates to understand why they chose OPIT, how they felt about the course, and what advice they might give to others considering studying at OPIT.

Karina is an experienced FinTech professional who is an experienced integration manager, ERP specialist, and business analyst. She was interested in learning AI applications to expand her career possibilities, and she chose OPIT’s MSc in Applied Data Science & AI.

In the interview, Karina discussed why she chose OPIT over other courses of study, the main challenges she faced when completing the course while working full-time, and the kind of support she received from OPIT and other students.

Why Study at OPIT?

Karina explained that she was interested in enhancing her AI skills to take advantage of a major emerging technology in the FinTech field. She said that she was looking for a course that was affordable and that she could manage alongside her current demanding job. Karina noted that she did not have the luxury to take time off to become a full-time student.

She was principally looking at courses in the United States and the United Kingdom. She found that comprehensive courses were expensive, costing upwards of $50,000, and did not always offer flexible study options. Meanwhile, flexible courses that she could complete while working offered excellent individual modules, but didn’t always add up to a coherent whole. This was something that set OPIT apart.

Karina admits that she was initially skeptical when she encountered OPIT because, at the time, it was still very new. OPIT only started offering courses in September 2023, so 2025 was the first cohort of graduates.

Nevertheless, Karina was interested in OPIT’s affordable study options and the flexibility of fully remote learning and part-time options. She said that when she looked into the course, she realized that it aligned very closely with what she was looking for.

In particular, Karina noted that she was always wary of further study because of the level of mathematics required in most computer science courses. She appreciated that OPIT’s course focused on understanding the underlying core principles and the potential applications, rather than the fine programming and mathematical details. This made the course more applicable to her professional life.

OPIT’s MSc in Applied Data Science & AI

The course Karina took was OPIT’s MSc in Applied Data Science & AI. It is a three- to four-term course (13 weeks), which can take between one and two years to complete, depending on the pace you choose and whether you choose the 90 or 120 ECTS option. As well as part-time, there are also regular and fast-track options.

The course is fully online and completed in English, with an accessible tuition fee of €2,250 per term, which is €6,750 for the 90 ECTS course and €9,000 for the 120 ECTS course. Payment plans are available as are scholarships, and discounts are available if you pay the full amount upfront.

It matches foundational tech modules with business application modules to build a strong foundation. It then ends with a term-long research project culminating in a thesis. Internships with industry partners are encouraged and facilitated by OPIT, or professionals can work on projects within their own companies.

Entry requirements include a bachelor’s degree or equivalency in any field, including non-tech fields, and English proficiency to a B2 level.

Faculty members include Pierluigi Casale, a former Data Science and AI Innovation Officer for the European Parliament and Principal Data Scientist at TomTom; Paco Awissi, former VP at PSL Group and an instructor at McGill University; and Marzi Bakhshandeh, a Senior Product Manager at ING.

Challenges and Support

Karina shared that her biggest challenge while studying at OPIT was time management and juggling the heavy learning schedule with her hectic job. She admitted that when balancing the two, there were times when her social life suffered, but it was doable. The key to her success was organization, time management, and the support of the rest of the cohort.

According to Karina, the cohort WhatsApp group was often a lifeline that helped keep her focused and optimistic during challenging times. Sharing challenges with others in the same boat and seeing the example of her peers often helped.

The OPIT Cohort

OPIT has a wide and varied cohort with over 300 students studying remotely from 78 countries around the world. Around 80% of OPIT’s students are already working professionals who are currently employed at top companies in a variety of industries. This includes global tech firms such as Accenture, Cisco, and Broadcom, FinTech companies like UBS, PwC, Deloitte, and the First Bank of Nigeria, and innovative startups and enterprises like Dynatrace, Leonardo, and the Pharo Foundation.

Study Methods

This cohort meets in OPIT’s online classrooms, powered by the Canvas Learning Management System (LMS). One of the world’s leading teaching and learning software, it acts as a virtual hub for all of OPIT’s academic activities, including live lectures and discussion boards. OPIT also uses the same portal to conduct continuous assessments and prepare students before final exams.

If you want to collaborate with other students, there is a collaboration tab where you can set up workrooms, and also an official Slack platform. Students tend to use WhatsApp for other informal communications.

If students need additional support, they can book an appointment with the course coordinator through Canvas to get advice on managing their workload and balancing their commitments. Students also get access to experienced career advisor Mike McCulloch, who can provide expert guidance.

A Supportive Environment

These services and resources create a supportive environment for OPIT students, which Karina says helped her throughout her course of study. Karina suggests organization and leaning into help from the community are the best ways to succeed when studying with OPIT.

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Leading in the Digital Age: Navigating Strategy in the Metaverse
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jun 5, 2025 5 min read

In April 2025, Professor Francesco Derchi from the Open Institute of Technology (OPIT) and Chair of OPIT’s Digital Business programs entered the online classroom to talk about the current state of the Metaverse and what companies can do to engage with this technological shift. As an expert in digital marketing, he is well-placed to talk about how brands can leverage the Metaverse to further company goals.

Current State of the Metaverse

Francesco started by exploring what the Metaverse is and the rocky history of its development. Although many associate the term Metaverse with Mark Zuckerberg’s 2021 announcement of Meta’s pivot toward a virtual immersive experience co-created by users, the concept actually existed long before. In his 1992 novel Snow Crash, author Neal Stephenson described a very similar concept, with people using avatars to seamlessly step out of the real world and into a highly connected virtual world.

Zuckerberg’s announcement was not even the start of real Metaverse-like experiences. Released in 2003, Second Life is a virtual world in which multiple users come together and engage through avatars. Participation in Second Life peaked at about one million active users in 2007. Similarly, Minecraft, released in 2011, is a virtual world where users can explore and build, and it offers multiplayer options.

What set Zuckerberg’s vision apart from these earlier iterations is that he imagined a much broader virtual world, with almost limitless creation and interaction possibilities. However, this proved much more difficult in practice.

Both Meta and Microsoft started investing significantly in the Metaverse at around the same time, with Microsoft completing its acquisition of Activision Blizzard – a gaming company that creates virtual world games such as World of Warcraft – in 2023 and working with Epic Games to bring Fortnite to their Xbox cloud gaming platform.

But limited adoption of new Metaverse technology saw both Meta and Microsoft announce major layoffs and cutbacks on their Metaverse investments.

Open Garden Metaverse

One of the major issues for the big Metaverse vision is that it requires an open-garden Metaverse. Matthew Ball defined this kind of Metaverse in his 2022 book:

“A massively scaled and interoperable network of real-time rendered 3D virtual worlds that can be experienced synchronously and persistently by an effectively unlimited number of users with an individual sense of presence, and with continuity of data, such as identity, history, entitlements, objects, communication, and payments.”

This vision requires an open Metaverse, a virtual world beyond any single company’s walled garden that allows interaction across platforms. With the current technology and state of the market, this is believed to be at least 10 years away.

With that in mind, Zuckerberg and Meta have pivoted away from expanding their Metaverse towards delivering devices such as AI glasses with augmented reality capabilities and virtual reality headsets.

Nevertheless, the Metaverse is still expanding today, but within walled garden contexts. Francesco pointed to Pokémon Go and Roblox as examples of Metaverse-esque words with enormous engagement and popularity.

Brands Engaging with the Metaverse: Nike Case Study

What does that mean for brands? Should they ignore the Metaverse until it becomes a more realistic proposition, or should they be establishing their Meta presence now?

Francesco used Nike’s successful approach to Meta engagement to show how brands can leverage the Metaverse today.

He pointed out that this was a strategic move from Nike to protect their brand. As a cultural phenomenon, people will naturally bring their affinity with Nike into the virtual space with them. If Nike doesn’t constantly monitor that presence, they can lose control of it. Rather than see this as a threat, Nike identified it as an opportunity. As people engage more online, their virtual appearance can become even more important than their physical appearance. Therefore, there is a space for Nike to occupy in this virtual world as a cultural icon.

Nike chose an ad hoc approach, going to users where they are and providing experiences within popular existing platforms.

As more than 1.5 million people play Fortnite every day, Nike started there, first selling a variety of virtual shoes that users can buy to kit out their avatars.

Roblox similarly has around 380 million monthly active users, so Nike entered the space and created NIKELAND, a purpose-built virtual area that offers a unique brand experience in the virtual world. For example, during NBA All-Star Week, LeBron James visited NIKELAND, where he coached and engaged with players. During the FIFA World Cup, NIKELAND let users claim two free soccer jerseys to show support for their favorite teams. According to statistics published at the end of 2023, in less than two years, NIKELAND had more than 34.9 million visitors, with over 13.4 billion hours of engagement and $185 million in NFT (non-fungible tokens or unique digital assets) sales.

Final Thoughts

Francesco concluded by discussing that while Nike has been successful in the Metaverse, this is not necessarily a success that will be simple for smaller brands to replicate. Nike was successful in the virtual world because they are a cultural phenomenon, and the Metaverse is a combination of technology and culture.

Therefore, brands today must decide how to engage with the current state of the Metaverse and prepare for its potential future expansion. Because existing Metaverses are walled gardens, brands also need to decide which Metaverses warrant investment or whether it is worth creating their own dedicated platforms. This all comes down to an appetite for risk.

Facing these types of challenges comes down to understanding the business potential of new technologies and making decisions based on risk and opportunity. OPIT’s BSc in Digital Business and MSc in Digital Business and Innovation help develop these skills, with Francesco also serving as program chair.

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