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Learn Python for Machine Learning

A Comprehensive Guide to Start Learning Python for Machine Learning

Python is a general-purpose, open-source programming language that has been in use for over 30 years. It is one of the most popular and commonly-used programming languages for machine learning. In this overview, you’ll learn more about Python for machine learning, what it can do, who uses it, and how to learn it to determine how to add this skill to your professional toolbox.

Python is a general-purpose programming language with several uses in the field of machine learning. If you’ve always wanted to learn Python for machine learning but can’t figure out how to get started, this guide is for you. Here, you’ll learn more about the various ways to learn Python for machine learning, free resources to take advantage of, and the types of careers that commonly use Python for machine learning.

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.

Careers that Use Python for Machine Learning

Machine learning is a coveted skill with applications in technology, finance, and healthcare. Python for machine learning can open the door to one of these exciting careers: 

  • Machine Learning Engineer 
  • Robotics Engineer 
  • Software Developer
  • Data Scientist 
  • Cybersecurity Analyst 
  • Artificial Intelligence (AI) Engineer 

A Machine Learning Engineer creates machine learning models, optimizes data delivery, and manages complex datasets. Machine Learning Engineers may choose to build machine learning components with Python programming due to Python’s popularity, simplicity, and many uses. The machine learning components reveal patterns and make predictions to help companies plan for success. Machine learning is also a critical skill for Robotics Engineers. 

Software Developers use Python for machine learning to improve the user experience in multiple ways. Python for machine learning can enable chatbots to communicate with users helpfully and naturally, recommend products or content based on a user’s interests, and predict how users will react to application features. 

Data Scientists use machine learning to write algorithms that detect trends. The Data Scientist then uses this information to make recommendations to stakeholders. 

Understanding machine learning benefits Cybersecurity Analysts when tasked with collecting and studying large quantities of data to detect potential security risks. Machine learning can make gathering, managing, and understanding this data easier.

AI Engineers use machine learning (a subset of AI) to build or modify machine learning models, develop neural network applications, and improve image recognition.

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.

How to Learn Python for Machine Learning

There are different ways of learning Python for machine learning, including live classes, on-demand classes, and free resources. This section explores each of these options in detail. 

Live classes, or instructor-led courses, include in-person classes and live online classes. With both methods, an expert instructor guides the class in real-time through lectures, examples, and hands-on assignments. Live classes provide the opportunity to instantly have your questions answers and to receive immediate feedback. You can also collaborate with classmates, walk through real-world projects with step-by-step guidance, and receive personalized instruction. You can find in-person and live online Python for machine learning classes using Noble Desktop’s Classes Near Me tool. 

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.

If you aren’t ready to commit to a paid learning option, you can explore free resources like seminars, tutorials, guides, videos, and blog posts. Noble Desktop’s Python for Machine Learning Hub connects you to multiple free resources to help you get started. If you are new to data science, the free video Get Started in Data Science provides a high-level overview of the field. When you feel ready to dive deeper into a topic, you can use the Noble Desktop Classes Near Me tool to explore machine learning classes available online and in your local area

Read the full guide on how to learn Python for machine learning.

Free Introductory Python for Machine Learning Course Online 

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.

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.

How Does Learning Python for Machine Learning Compare to Other Languages?

Python, Java, and R are all popular programming languages used in data science. Each coding language has its benefits and drawbacks, which this section discusses in detail. This section also compares the difficulty of learning each of these programming languages. 

Java is a concurrent, general-purpose, class-based, and object-oriented programming language. Java works best for large-scale projects but does not perform as well as Python and R when used for statistical monitoring. Java is not considered complex or challenging to learn. 

Python provides the most flexible solution for workflow integrations, allowing you to integrate data analysis and statistical method features with a web app or production environment. Python libraries like scikit-learn and PyBrain can be used to build prediction engines and models that you can easily integrate into the production environment. Python is considered a beginner-friendly coding language, but as with any programming language, hands-on experience is essential to committing skills to memory. 

R was created for detailed statistical analysis. This coding language is ideal for data science reports thanks to its ability to create high-quality graphics and charts, but R does run slower than either Python or Java. R is considered a difficult programming language to learn. 

Whether you want to learn Java, Python, or R, having an instructor to guide you through real-world, hands-on projects can help you learn faster and solidify your skills. Learn more about machine learning and the professions that use it, and compare different machine learning skills with Noble Desktop’s machine learning resources

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.

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