How to Learn Python for Machine Learning

Python for machine learning is a valued skill among Data Scientists and Data Analysts. Understanding Python for machine learning can advance your current career or help you learn something new. Machine learning is an increasingly important tool used by organizations across numerous industries. The number of options for learning Python for 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 Python for machine learning so you can decide how you’d like to get started.

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.

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 Python for Machine Learning Classes

On-demand courses are also known as self-paced courses because they have few, if any, hard deadlines, relying on you to advance at your own pace. This flexibility works well for those with an unconventional or packed schedule. On-demand courses consist primarily of video content, which allows you to pause and rewatch lessons whenever you wish. You can explore free video content covering introductory topics such as Python basics or advanced topics like Python for machine learning. You can also find paid video courses on platforms like Coursera, Udemy, and LinkedIn Learning for around $30 to $60 per month, making this educational option highly affordable. 

The main drawback to keep in mind when exploring on-demand training options is that self-paced classes often lack instructor access. If you have a question or have technical issues, you may have to wait several hours or days to receive an email reply. And the more complex a topic is, the more beneficial it is to have real-time feedback from an instructor. Still, on-demand classes can benefit in learning introductory skills and gaining a high-level overview of a topic before committing to a more expensive training method.

Learn more about on-demand Python for machine learning courses.

Which Learning Method is Right for Me?

With so many different resources available to help beginners learn Python for machine learning, you might need clarification on which one is best for you. Everyone has different learning styles and preferences, and you can experiment with multiple tools to see which one feels right for you. One of the great things about directing your own learning is that you get to pick which combination of tools you prefer; you don’t have to stick with what a teacher 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 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. 

To determine the best learning method for you, you can start with determining your learning style. Do you learn best by doing, seeing, hearing, or some combination of the three? Kinesthetic or tactile learners retain information by gaining hands-on experience. Visual learners retain information by seeing it. Auditory learners retain information by hearing it. For kinesthetic learners, Python for machine learning classes should involve hands-on projects. Visual and auditory learners can benefit from live online classes that combine lectures with visualizations. They may also appreciate on-demand video content that can be paused and replayed. Most people do not fall neatly into one learning type but benefit from a combined learning approach. Instructor-led classes combine lectures, visual elements, and hands-on experience under the guidance of an expert.

Another consideration is whether you want to enroll full-time or part-time. Most students choose part-time enrollment because this schedule allows them to balance full-time jobs with classwork. However, if you can enroll in a full-time course, you can finish your class or program much sooner. Therefore, full-time enrollment works well for those eager to pursue a new career as soon as possible.

You will also want to consider your budget. When researching the cost of different learning methods, remember that the upfront costs might not reflect the better long-term investment. A less expensive training option may provide a limited amount of instruction and experience compared to a more expensive one. For example, a one-day class will cost far less than a six-month program due to the difference in length. However, a one-day class will not be sufficient to launch a new career, whereas a six-month program could help you start an entirely new profession. Also research the average salaries for the career you intend to pursue. Compare this potential income to the cost of your tuition to determine how soon your investment in your education would pay off. You can also search for classes and programs that offer flexible payment plans, reducing upfront costs.

Some in-person and live online classes include 1-on-1 mentoring. Small class sizes are fantastic for receiving individualized feedback, but mentorship provides even more personalized instruction and advice. You can use 1-on-1 sessions with your mentor to ask questions, review your projects, and learn from your mentor’s professional experience. Mentoring can help you articulate your career goals, create a plan to reach them, and help you network professionally. Understanding your goals and how to reach them plays a huge part in advancing your career or launching a new one. A mentor can also help you prepare for a new career by reviewing your resume and portfolio. 

You might wonder if you need a portfolio to find a job that uses Python for machine learning. Most people who learn Python for machine learning seek careers as Data Scientists, Data Analysts, or Software Engineers. When you apply for such a position, especially if you are pivoting into a new career, employers want to see evidence of your knowledge and skills. A portfolio provides proof of your abilities and demonstrates your capabilities to employers. Look for a class that includes projects you can add to your professional portfolio. Classes and programs that include portfolio review will help make sure you showcase your very best work.

Other job assistance benefits included in a course can go a long way to helping you launch a new career. Often, finding a job comes down to who you know. In-person classes offer the chance to network with local professionals such as classmates and instructors. Live online classes can also help you find a job through services like resume review, portfolio review, mock interviews, 1-on-1 mentorship, and other job search assistance benefits. Part of choosing between an in-person or live online class will depend on if you wish to confine your job search to your current area or if you would be open to building connections in other areas or for remote positions. 

Noble Desktop can connect you to on-demand resources, in-person classes, and live online classes. You can explore the Machine Learning Hub to learn more about Python, machine learning, and training methods. On-demand videos benefit visual and auditory learners and can be excellent resources for gaining high-level overviews, reviewing information, or supplementing other class types. For skills that require hands-on experience to master, such as Python for machine learning, instructor-led courses provide expert guidance through in-person classes and live online classes. You are also not limited to any one learning method and can find ways of combining different methods for a plan tailored to your needs.

Why Learn Python for Machine Learning?

Machine learning is an increasingly important component in personalizing and improving user experience and automating tasks. Machine learning algorithms are used to make product recommendations to shoppers on Amazon, manage trading on Wall Street, and choose what plans next in your Spotify playlist. 

Learning Python for machine learning can advance your current career or help you start a new one. Employers look for this highly desirable skill when hiring Data Analysts and Data Scientists, so learning Python for machine learning can help your resume stand out. If you learn Python for machine learning through an instructor-led course with hands-on projects, you can add those projects to your professional portfolio to showcase your abilities to potential employers.

Level of Difficulty, Prerequisites, & Cost 

Before learning Python for machine learning, you must demonstrate a solid understanding of Python programming and the NumPy and Pandas libraries. While many consider Python a relatively easy coding language for experienced programmers to learn, it can prove challenging, especially for students new to coding. If you do not have a background in data science, learning Python and machine learning as part of a data science certificate program can help you build data science skills, starting with the fundamentals, then building your way up to topics like machine learning. 

The Python programming language is an open-source coding language, meaning that anyone can download it for free. You can find the latest version of Python, view documentation, join the Python community, and more through the Python Software Foundation’s website. 

Read about how difficult it is to learn Python for machine learning.

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.

Key Insights

• Python is a free, open-source programming language. This general-purpose programming language has artificial intelligence capabilities including machine learning. 
• Machine learning is the field of inquiry concerned with automatically performed data-based tasks. Machine learning recommends products based on browsing history, chooses new songs to add to your music streaming queue, performs facial recognition, and more.
• Data Scientists and Data Analysts often use Python for machine learning, so adding this skill to your resume can help you start a data science career.
• Keep your schedule, budget, and learning style in mind when considering what learning method to pursue. 
• You can receive comprehensive Python for machine learning training through an in-person or live online course with Noble Desktop.