How to Learn Machine Learning

Thanks to its massive growth throughout numerous industries, the multidisciplinary machine learning (ML) field now attracts more tech professionals than ever. If you’re looking for a rewarding career, consider machine learning. The number of options for learning machine learning might be overwhelming at first glance. There are books, video tutorials, classes, and more to choose from; it all depends on your learning style and personal preferences.

Here, we’ll discuss the various methods of learning machine learning so you can make an informed decision about how you’d like to get started.

What is Machine Learning?

Machine learning (ML) is one of the best-known subcategories of artificial intelligence (AI). This complex and multidisciplinary field can require training in programming languages like Python, databases like MySQL, and natural language processing (NLP). Common careers that require machine learning skills include Machine Learning Engineers, Data Scientists, and Business Intelligence (BI) Analysts.

Machine learning is often associated with Python programming and data science. Supervised, unsupervised, and reinforcement learning are the top three models of ML algorithms. Popular uses of ML in daily activities include voice recognition tools like Siri, recommendation lists from Amazon or Netflix, and user engagement icons on platforms like Instagram and TikTok. 

Read more about what machine learning is and why you should learn it. 

What Can You Do with Machine Learning?

Machine learning algorithms dominate today’s internet. Websites gather information based on everything you do online, from your search patterns to previous purchases, social media posts, and whether or not you abandon a product in a cart. As ML algorithms continue to influence our personal and professional lives, more and more businesses use them to streamline processes and determine customer and client journeys. The following are a few of the most popular machine learning applications.

• Social media - Meta Platforms (formerly Facebook) was one of the first well-known companies to use ML to measure user activities. Examples of how they analyze statistical activity include their user engagement, chatbots, and content filtering features. Other top social media platforms using ML extensively include Twitter, Pinterest, and TikTok.

• Product Recommendations - If you’ve ever bought a product from Amazon or subscribed to a streaming service, you’ve probably seen the You May Like feature. Companies ranging from Apple to Netflix use machine learning algorithms to customize your experience.

• Natural Language Processing (NLP) involves text analytics and functions combined with machine learning. Analyzing text includes basic steps like identifying the language and more complex steps like syntax parsing and sentiment analysis. ML is essential to text analytics and NLP solutions.

In-Person Machine Learning Training

If you’re ready for a machine learning course, you might start by looking in your area for an in-person program. While attitudes toward online learning have grown increasingly positive in recent years, many students feel that face-to-face training engages them more than any other alternative. In-person coursework gives attendees the most direct way to interact with other students and instructors, and a short commute can be well worth the effort. Others may think of a commute as a drawback or cannot find appropriate training close to home. Still, if you feel it best matches your learning style, consider an in-person program your first choice. 

Noble Desktop hosts many of its top machine learning and data science bootcamps at its Madison Avenue campus in New York City. If you’re in NYC, you can take advantage of their Python for Data Science Bootcamp, Python Machine Learning Bootcamp, or Data Science Certificate program. These intensive courses feature machine learning training as part of a broader curriculum, like Python fundamentals, data visualization and analysis, and linear regression. 

Other in-person programs include a Machine Learning Immersive from Practical Programming, Advanced Data Analytics from Skillspire, and Applied Machine Learning & Data Science with Python from Emory Continuing Education. Check listings for training locations and any prerequisite information.

Live Online Machine Learning Training

Once you have a solid idea of how you plan to use your machine learning training, it’s time to look at some of the best ways you can learn it in more detail. The best bootcamps and certificate programs offer hands-on training in an interactive environment. Online training offers other benefits: you can learn from the comfort of your home or office, and in some cases, the instructor can even share the screen with your permission.

Noble Desktop offers many of its most popular bootcamps and certificates live online or in-person at its world-class New York training center. That means you can take these courses from wherever you are and learn in real-time without commuting. Consider the benefits of some of their best machine learning programs:

• Data Science Certificate - The Data Science Certificate from Noble Desktop includes everything from Python to intensive SQL training. You’ll apply machine learning models with the Scikit-learn library, analyze data with NumPy and Pandas, and automate everyday tasks with Python. Whether you’re planning a Python engineering career or want to learn ML as part of a broader data science curriculum, this certificate will prepare you for success.

• Python Machine Learning Bootcamp - Noble’s Python Machine Learning Bootcamp gives Python Developers the tools they need to explore machine learning algorithms in an interactive environment. You can also save by taking this bootcamp as part of the Data Science Certificate program. Check course listings for details, including prerequisite information.

• Python Data Science & Machine Learning Bootcamp - The Python Data Science & Machine Learning Bootcamp combines machine learning training with Python programming tools like Pandas, NumPy, and Matplotlib. Like the Data Science Certificate, this immersive program is open to beginners and is available online and at Noble Desktop’s New York City location.

Other live online machine learning courses include an Applied Machine Learning class from WeCloudData, Python for Data Science and ML from Promotable, and Practical Programming’s Machine Learning Immersive.

Free Online Courses & Tutorials

Not ready to take a full-length machine learning course? If you’re not able to commit to a full-length bootcamp or certificate, you should consider the many free online resources you can use to start studying machine learning.

One of the most important areas of study for those new to machine learning is technical proficiency in a free programming language like Python. If you don’t already have Python experience, it can be helpful to learn more about it before you dive into the study of machine learning. 

Noble Desktop hosts an online seminar entitled Intro to Python Fundamentals. In this free introductory course, you’ll learn about the practical uses of Python. The curriculum walks new programmers through every step to get started in Python programming—from how to install Python to how to write code.

Other free online courses include Introduction to Embedded Machine Learning from Edge Impulse, Artificial Intelligence: Ethics & Societal Challenges from Lund University, and the University of London’s Foundations of Data Science: K-Means Clustering in Python.

Read about more free machine learning videos and online tutorials.

On-Demand Machine Learning Classes

On-demand or self-paced machine learning training offers another way to learn about this exciting field. These courses range from one-hour video tutorials to programs that take six months or longer. Topics include machine learning using Azure, programming languages like Python and R, and frameworks like TensorFlow and PyTorch. Some classes are free, while others require a fee or subscription to a platform. As in other training options, some on-demand courses are open to beginners. Others offer training at the intermediate level, and some provide advanced machine learning training.

This type of training has its own built-in set of advantages and drawbacks. While self-paced training can be a convenient way to begin studying the machine learning field, the lack of accountability or instructor feedback can create obstacles for you unless you are highly self-motivated and disciplined. As a starting point, however, on-demand video courses can give you valuable tools that prepare you for formal training with an instructor.

On-demand training includes options like 1-hour machine learning videos from Skillshare, beginner, intermediate, and advanced training videos from DataCamp, and an advanced six-month ML Engineering Career Track program from Springboard.

Which Learning Method is Right for Me?

With so many different resources available to help beginners master machine learning, you might be unsure which one is best for you. Everyone has different learning styles and preferences, and you can experiment with multiple resources to see which one feels right for you. One of the great things about directing your learning is that you can decide what combination of tools you prefer; you don’t have to stick with what an instructor chooses.

It’s also essential to consider your current schedule before selecting a learning method. If you have a lot of responsibilities like a full-time job or family commitments, you may not be able to devote time to a structured machine learning course that requires you to attend at the same time every day. In this case, a self-paced class or video tutorials may be better since you can access them when your schedule allows. On the other hand, those with a more flexible schedule may prefer a structured course offered in-person or live online. 

Why Learn Machine Learning?

Machine learning programs have become so common that you most likely interact with them daily. Consider Amazon’s “Compare Similar Items” feature, the “Because You Watched” recommendations on Netflix, and the recommended reels on your Instagram feed. All of these tools come from machine learning algorithms.

If you’re planning to start a career in data science or analytics, ML can be a core segment of your education. Anyone with a title like Data Scientist or Data Engineer should be familiar with machine learning concepts. A Machine Learning Engineer or Machine Learning Architect must have a specialized skill set in subjects like deep learning, data modeling, and natural language processing (NLP).

Read more about why you should learn machine learning. 

Level of Difficulty, Prerequisites, & Cost 

Studying machine learning (ML) can be a lifelong pursuit. The challenges of learning this topic depend on how much you need to learn and where you will apply it. 

You may have more challenges learning ML if you lack experience with algorithms or have little familiarity with programming languages like Python. Consider learning these through a course that features them or includes them as part of a broader computer or data science curriculum.

Machine learning training costs range from free to around about $1,895 to $4,495 for a bootcamp or certificate program. Some of these courses include intensive ML training and can be completed in a few months or weeks.

Read about how difficult it is to learn machine learning.

Learn Machine Learning with Hands-on Training at Noble Desktop

Noble Desktop offers a variety of bootcamps and certificates that feature machine learning, both in-person and live online via teleconferencing. Some include Python as a focus, others include machine learning as part of a broader data science curriculum, and others cover ML in a FinTech curriculum. All bootcamps and certificate programs feature small class sizes to maximize personal attention from expert instructors.

• Data Science Certificate - Noble’s Data Science Certificate program teaches participants data science fundamentals before advancing through machine learning, Python for automation, and Structured Query Language (SQL). This immersive certificate is open to beginners; you can retake it for up to one year at no additional charge.

• Python Machine Learning Bootcamp - Programmers already comfortable with Python and its data science libraries can get their machine learning training as part of the Python Machine Learning Bootcamp. Attendees can save by taking this shorter course as part of the Data Science Certificate program.

• Python Data Science & Machine Learning Bootcamp - This comprehensive bootcamp combines the same ML and Python training modules as the Data Science Certificate but does not include the Structured Query Language (SQL) bootcamp. It’s open to beginners and designed to prepare students for entry-level Python engineering or data science positions. 

For more information on Noble Desktop’s data science classes, including machine learning, check out all their full-time and part-time data science programs.

Key Insights

• Machine learning (ML) is one of the most important subcategories of artificial intelligence (AI). Popular uses of ML in everyday consumer activities include:
• Voice recognition tools (Siri, Alexa)
• Recommendation lists (Amazon, Netflix)
• User engagement (Likes on platforms such as Instagram and TikTok)
• Top uses of machine learning in professional situations include:
• Customer service chatbots
• Content filtering features
• Natural language processing (NLP)
• Training methods for machine learning include:
• In-person bootcamps and certificate programs
• Live online bootcamps, certificates, or individual classes
• Free video tutorials and seminars
• On-demand or self-paced courses
• Prerequisites for machine learning training can include computer programming, strong communication skills, and familiarity with statistics and probability. 
• Consider your personal learning style when determining which method is best for you.
• You can receive comprehensive machine learning training through an in-person or live online course with Noble Desktop.