Which Python for Machine Learning Training Format Is Right for Me?

Python is a general-purpose programming language commonly used for machine learning. You might wonder what kinds of training methods are available for learning Python. When comparing types of Python for machine learning training, there are many factors to consider. Everyone learns differently, and choosing the right kind of training is critical to your experience.

Keep reading to learn more about Python's different formats for machine learning training, how they compare to each other, and how to determine which is best for you.

What is Python for Machine Learning?

Python is an open-source, general-purpose programming language first developed in 1991. Because Python is open-source, it is free and publicly available for anyone to use. Python can be used to build websites, develop software, conduct data analysis, and automate tasks using artificial intelligence (AI) and machine learning. 

Machine learning enables computer systems to automatically learn and adapt without manual input. The system does this by using statistical models and algorithms to detect patterns in data. Python’s libraries and frameworks, along with the coding language’s platform independence, popularity and community, concise and readable code, flexibility, and consistency, make it a perfect fit for machine learning. 

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

What Can You Do with Python for Machine Learning?

Python is a general-purpose programming language that you can use to create data visualizations, write programs for machine learning, analyze data, make file directories, build apps, and more. Because of its many applications in using and managing data, Data Scientists must have a thorough knowledge of Python programming and its uses. 

Python for machine learning is used to personalize and improve user experiences. Machine learning can automate customer support, detect fraudulent transactions, recommend products, refine search engine results, automate translation, recommend music, and predict the effectiveness of drug treatments. There are countless uses for machine learning and demand is only increasing, making now an opportune time to learn Python for machine learning.

Training Formats for Python for Machine Learning

You can choose from several training types when learning Python and machine learning skills. You can also combine learning methods for a training plan that suits your needs. The following sections offer details on in-person classes, live online classes, and on-demand/self-paced classes.

In-Person Python for Machine Learning Training

In-person training allows you to learn Python for machine learning at a physical location. You can learn from an expert instructor face-to-face, collaborate with classmates on hands-on activities, network with local professionals, and access all necessary equipment and software in the classroom. Some points to consider with this type of learning include commuting to your classroom location, which eats up additional time. You will also need to factor the cost of transportation into your budget. One limitation of the in-person learning method is that you may have only a small number of classes to choose time, so finding a curriculum that covers everything you want to learn or a class time that works for your schedule might be difficult. You can research and compare in-person classes available in your area to determine which class meets your needs. 

The Classes Near Me tool from Noble Desktop lets you compare in-person classes side-by-side. You can research curriculums, costs, and other facts about classes in your area. For example, Python machine learning classes that meet in-person in New York City or meet live online include Noble Desktop’s Python for Data Science Bootcamp and Python Machine Learning Bootcamp, the Data Science with R: Machine Learning course from NYC Data Science Academy, Practical Programming’s Machine Learning Immersive, and more.

Live Online Python for Machine Learning Training

When researching Python for machine learning, you may wonder if live online classes are the best way to learn. Live online classes come with many benefits, but there are also a few drawbacks to consider. Benefits include collaborating with classmates, asking your instructor questions in real-time, and getting instant step-by-step guidance on hands-on assignments. Other positives include the ability to learn remotely so you never have to commute and you can choose from classes offered worldwide. Drawbacks to the live online training format are that classes meet at a designated time, which is difficult if you have a packed schedule, and that unlike in-person classes, live online classes do not offer the chance to network on the local level. You will also need to ensure that you have all the necessary equipment and software to complete your live online class, which can be an extra expense. For most students, the positives far outweigh the negatives when taking a live online class. You can also get the most out of your live online class by finding courses with additional benefits like flexible payment plans, free retakes, 1-on-1 mentoring, and job search assistance.

You can use the Classes Near Me tool to explore and compare live online Python for machine classes.

Free Online Courses & Tutorials

Before committing to a paid training method, you may want to explore free resources that provide an overview of Python for machine learning. Free resources can help you build foundational skills, understand the advantages and challenges of learning Python for machine learning, meet the necessary prerequisites, and help you decide how you want to learn this skill. 

Before learning Python for machine learning, you must have a firm foundation in Python programming and understand the NumPy and Pandas libraries. In Noble Desktop’s free video seminar Intro to Python Fundamentals, you will learn about the Python programming language and its many uses in data science and data analytics.

You can also find free introductory Python courses from Google, Microsoft, and on learning platforms like Udemy and Coursera.

Read about more free Python for machine learning videos and online tutorials.

On-Demand Classes

You can also explore Python for machine learning topics through on-demand (self-paced) classes. These classes, also known as asynchronous classes, consist of on-demand videos and materials that you advance through at your own pace. The flexibility to completely control your schedule and the affordability of such courses make them a popular learning option. You can explore and compare on-demand machine learning classes to find the best fit for your needs.

Comparison of Python for Machine Learning Training Formats

When comparing available training methods for machine learning with Python, you should consider the benefits and drawbacks of each format. Also consider your learning style, schedule, career goals, and budget. The three training methods are on-demand, in-person, and live online classes. This section will compare each training format to help you choose the best fit for your needs. 

On-demand/self-paced classes primarily consist of pre-recorded video content. The self-paced nature of these courses and their affordability make them a popular learning method. You can explore free on-demand classes on Python and machine learning or complete paid courses through subscriptions to platforms like Udemy, LinkedIn Learning, and Coursera. These paid subscriptions cost around $30 to $60 per month. Some courses take multiple months to complete, making this a recurring rather than a one-time payment. Videos are easy to view on desktop and mobile devices. They provide visual and audible content, which benefits visual and auditory learners. You can also pause and replay the video as often as you need, which helps you retain the information long-term. This learning method's main drawback is having no instructor access or very limited access. When you are stuck waiting hours or days for an emailed response to your question, it grinds all progress to a halt. For this reason, many people use on-demand classes to introduce a topic, then follow up with instructor-led courses. 

Instructor-led courses include in-person classes and live online classes. Both formats are led by instructors in real-time, allow you to interact and collaborate with classmates, and provide instant feedback when you have questions or are working through a hands-on activity. In-person classes have the advantage of letting you network locally and providing all necessary equipment, such as a computer loaded with the tools you need. Live online classes can let you learn from anywhere, with no need to commute. With live online classes, you can enroll in courses based in distant places, which gives you a much wider selection of available courses. Whether you meet in person or live online, you will want to find a class time that works for your schedule and a curriculum that covers the skills needed to reach your career goals. Also, consider whether part-time or full-time enrollment fits your needs. Part-time classes tend to meet in the evenings and on weekends, making it more convenient for those with weekday jobs. If you can commit to a full-time class schedule, you can typically complete a program in half the time, for example, reducing a six-month program to three months.

Is it Possible to Teach Yourself Python for Machine Learning?

Python is considered an easy and beginner-friendly programming language, however, its machine learning applications can prove more complicated. Many people benefit by gaining a high-level overview and learning some Python basics, then building upon that foundation with an instructor-led course. 

Videos, tutorials, free documentation, and other free learning resources can introduce you to Python and Python for machine learning. Once you are ready to start gaining hands-on experience, enrolling in an in-person class or live online class connects you with an instructor. The main benefit of working with an instructor is receiving real-time feedback and hands-on experience. If a question comes up while you are working through an exercise, you can have it answered right away. You can also ask your instructor about recommended methods and best practices, and receive personalized feedback to help you advance your skills. 

How to Decide the Best Way to Learn Python for Machine Learning

Deciding how you want to gain Python machine learning skills starts with knowing what you want to use these skills for. Are you advancing your current career? Are you looking to start a new career in data analytics or data science? Your chosen training method will depend on your skills and career goals. You will also want to consider what learning style suits you best. 

If you are curious about machine learning, but not ready to commit to a paid learning method yet, you can explore the subject through no-cost resources including free Python for machine learning videos and online tutorials.

If you already know how to program with Python, you can take a class or bootcamp specifically about machine learning with Python, such as Noble Desktop’s Python Machine Learning Bootcamp. If you are new to Python programming, a multi-focus course such as Noble’s Python for Data Science & Machine Learning Bootcamp starts with Python programming fundamentals and advances to machine learning. 

Those new to data analytics or data science may benefit from a program that covers several data science skills. Noble’s Data Science Certificate program covers programming fundamentals, machine learning models, data visualizations and interactive dashboards, and other essential data science skills. 

You will want to compare classes and curriculums and keep in mind how you learn best and what fits your schedule. Live online classes save time over in-person classes by removing the need to commute. However, in-person classes offer the opportunity to network locally. Live online classes also provide options beyond classes offered in your local area. Both class types provide real-time feedback and hands-on experience. Some programs also include benefits like 1-on-1 mentoring and job search assistance, which are especially useful if starting a new career.

Learn Python for Machine Learning with Hands-on Training at Noble Desktop

Noble Desktop offers instructor-led courses that provide hands-on experience using Python for machine learning. You can take a specialized course such as the Python for Machine Learning course or learn this skill through the Data Science Certificate program. 

The Python for Machine Learning course requires students to have a strong foundation in Python programming and its data science libraries NumPy and Pandas prior to enrollment. If you do not have previous experience with Python programming, you can satisfy this prerequisite by first taking Noble’s Python for Data Science Bootcamp.

If you want to learn Python for machine learning as part of a broader curriculum, especially if you want to launch a new career in data science, the Data Science Certificate program covers essential skills in a single program. This program includes small classes, 1-on-1 mentoring, setup assistance, a free retake, flexible payment options, hands-on experience, and job search assistance.

Explore live online Python for machine learning classes that connect you to expert instructors for real-time feedback and guidance.