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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Il Sole 24 Ore: 100 thousand IT professionals missing
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 14, 2024 6 min read

Written on April 24th 2024

Source here: Il Sole 24 Ore (full article in Italian)


Open Institute of Technology: 100 thousand IT professionals missing

Eurostat data processed and disseminated by OPIT. Stem disciplines: the share of graduates in Italy between the ages of 20 and 29 is 18.3%, compared to the European 21.9%

Today, only 29% of young Italians between 25 and 34 have a degree. Not only that: compared to other European countries, the comparison is unequal given that the average in the Old Continent is 46%, bringing Italy to the penultimate place in this ranking, ahead only of Romania. The gap is evident even if the comparison is limited to STEM disciplines (science, technology, engineering and mathematics) where the share of graduates in Italy between the ages of 20 and 29 is 18.3%, compared to the European 21.9%, with peaks of virtuosity which in the case of France that reaches 29.2%. Added to this is the continuing problem of the mismatch between job supply and demand, so much so that 62.8% of companies struggle to find professionals in the technological and IT fields.

The data

The Eurostat data was processed and disseminated by OPIT – Open Institute of Technology. an academic institution accredited at European level, active in the university level education market with online Bachelor’s and Master’s degrees in the technological and digital fields. We are therefore witnessing a phenomenon with worrying implications on the future of the job market in Italy and on the potential loss of competitiveness of our companies at a global level, especially if inserted in a context in which the macroeconomic scenario in the coming years will undergo a profound discontinuity linked to the arrival of “exponential” technologies such as Artificial Intelligence and robotics, but also to the growing threats related to cybersecurity.

Requirements and updates

According to European House Ambrosetti, over 2,000,000 professionals will have to update their skills in the Digital and IT area by 2026, also to take advantage of the current 100,000 vacant IT positions, as estimated by Frank Recruitment Group. But not only that: the Italian context, which is unfavorable for providing the job market with graduates and skills, also has its roots in the chronic birth rate that characterizes our country: according to ISTAT data, in recent years the number of newborns has fallen by 28%, bringing Italy’s birth rate to 1.24, among the lowest in Europe, where the average is 1.46.

Profumo: “Structural deficiency”

“The chronic problem of the absence of IT professionals is structural and of a dual nature: on one hand the number of newborns – therefore, potential “professionals of the future” – is constantly decreasing; on the other hand, the percentage of young people who acquires degrees are firmly among the lowest in Europe”, declared Francesco Profumo, former Minister of Education and rector of OPIT – Open Institute of Technology. “The reasons are varied: from the cost of education (especially if undertaken off-site), to a university offering that is poorly aligned with changes in society, to a lack of awareness and orientation towards STEM subjects, which guarantee the highest employment rates. Change necessarily involves strong investments in the university system (and, in general, in the education system) at the level of the country, starting from the awareness that a functioning education system is the main driver of growth and development in the medium to long term. It is a debated and discussed topic on which, however, a clear and ambitious position is never taken.”

Stagnant context and educational offer

In this stagnant context, the educational offer that comes from online universities increasingly meets the needs of flexibility, quality and cost of recently graduated students, university students looking for specialization and workers interested in updating themselves with innovative skills. According to data from the Ministry of University and Research, enrollments in accredited online universities in Italy have grown by over 141 thousand units in ten years (since 2011), equal to 293.9%. Added to these are the academic institutions accredited at European level, such as OPIT, whose educational offering is overall capable of opening the doors to hundreds of thousands of students, with affordable costs and extremely innovative and updated degree paths.

Analyzing the figures

An analysis of Eurostat statistics relating to the year 2021 highlights that 27% of Europeans aged between 16 and 74 have attended an entirely digital course. The highest share is recorded in Ireland (46%), Finland and Sweden (45%) and the Netherlands (44%). The lowest in Romania (10%), Bulgaria (12%) and Croatia (18%). Italy is at 20%. “With OPIT” – adds Riccardo Ocleppo, founder and director – “we have created a new model of online academic institution, oriented towards new technologies, with innovative programs, a strong practical focus, and an international approach, with professors and students from 38 countries around the world, and teaching in English. We intend to train Italian students not only on current and updated skills, but to prepare them for an increasingly dynamic and global job market. Our young people must be able to face the challenges of the future like those who study at Stanford or Oxford: with solid skills, but also with relational and attitudinal skills that lead them to create global companies and startups or work in multinationals like their international colleagues. The increasing online teaching offer, if well structured and with quality, represents an incredible form of democratization of education, making it accessible at low costs and with methods that adapt to the flexibility needs of many working students.”

Point of reference

With two degrees already starting in September 2023 – a three-year degree (BSc) in Modern Computer Science and a specialization (MSc) in Applied Data Science & AI – and 4 starting in September 2024: a three-year degree (BSc) in Digital Business, and the specializations (MSc) in Enterprise Cybersecurity, Applied Digital Business and Responsible Artificial Intelligence (AI), OPIT is an academic institution of reference for those who intend to respond to the demands of a job market increasingly oriented towards the field of artificial intelligence. Added to this are a high-profile international teaching staff and an exclusively online educational offer focused on the technological and digital fields.

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Times of India: The 600,000 IT job shortage in India and how to solve it
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 2, 2024 3 min read

Written on April 25th 2024

Source here: Times of India 


The job market has never been a straightforward path. Ask anyone who has ever looked for a job, certainly within the last decade, and they can tell you as much. But with the rapid development of AI and machine learning, concerns are growing for people about their career options, with a report from Randstad finding that 7 in 10 people in India are concerned about their job being eliminated by AI.

 Employers have their own share of concerns. According to The World Economic Forum, 97 million new AI-related jobs will be created by 2025 and the share of jobs requiring AI skills will increase by 58%. The IT industry in India is experiencing a tremendous surge in demand for skilled professionals on disruptive technologies like artificial intelligence, machine learning, blockchain, cybersecurity and, according to Nasscom, this is leading to a shortage of 600,000 profiles.

 So how do we fill those gaps? Can we democratize access to top-tier higher education in technology?

These are the questions that Riccardo Ocleppo, the engineer who founded a hugely successful ed-tech platform connecting international students with global Universities, Docsity, asked himself for years. Until he took action and launched the Open Institute of Technology (OPIT), together with the Former Minister of Education of Italy, Prof. Francesco Profumo, to help people take control of their future careers.

OPIT offers BSc and MSc degrees in Computer Science, AI, Data Science, Cybersecurity, and Digital Business, attracting students from over 38 countries worldwide. Through innovative learning experiences and affordable tuition fees starting at €4,050 per year, OPIT empowers students to pursue their educational goals without the financial and personal burden of relocating.

The curriculum, delivered through a mix of live and pre-recorded lectures, equips students with the latest technology skills, as well as business and strategic acumen necessary for careers in their chosen fields. Moreover, OPIT’s EU-accredited degrees enable graduates to pursue employment opportunities in Europe, with recognition by WES facilitating transferability to the US and Canada.

OPIT’s commitment to student success extends beyond academics, with a full-fledged career services department led by Mike McCulloch. Remote students benefit from OPIT’s “digital campus,” fostering connections through vibrant discussion forums, online events, and networking opportunities with leading experts and professors.

Faculty at OPIT, hailing from prestigious institutions and industry giants like Amazon and Microsoft, bring a wealth of academic and practical experience to the table. With a hands-on, practical teaching approach, OPIT prepares students for the dynamic challenges of the modern job market.

In conclusion, OPIT stands as a beacon of hope for individuals seeking to future-proof their careers in technology. By democratizing access to high-quality education and fostering a global learning community, OPIT empowers students to seize control of their futures and thrive in the ever-evolving tech landscape.

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