Python for Machine Learning & Data Science Course

Data scientists and software developers are growing at a rate significantly faster than the average, according to the U.S. Bureau of Labor Statistics, with an average of 200,000 combined annual job openings projected through 2033. Paired with six-figure salaries, now is a great time to join this in-demand industry.

This Python course is designed for those who want to learn how to work with data from the ground up with no prior coding experience. The course starts by covering the basics of Python programming before moving into more core data science skills like statistical analysis and regression modeling. From there, you will gain hands-on experience building classification models, tuning machine learning algorithms, and even training neural networks using Keras and TensorFlow.

During this Python training program, you will complete practical projects that mirror real-world data workflows, such as employee retention prediction, car pricing models, and image recognition using the MNIST dataset. These projects help reinforce skills and serve as portfolio pieces for job applications. The data science and machine learning training curriculum is structured to help you build confidence in using Python for data analysis and machine learning, even if you have no technical background.

What you will learn

• Python fundamentals such as variables, data types, functions, loops, and control flow
• Create and manipulate DataFrames using Pandas and perform exploratory data analysis (EDA)
• Perform linear regression and evaluate models using a train-test split and residuals
• Build and tune k-nearest neighbors models and explore feature scaling and distance metrics
• Train ensemble models like random forests using scikit-learn and practice neural network design in TensorFlow
• Submit predictions to real-world datasets using Kaggle workflows and build professional dashboards

How you will benefit

• Advanced your skill set with beginner-friendly Python and data science training, with no experience required
• Review lessons focusing on practical skills that employers are looking for when hiring data and machine learning experts
• Develop in-demand skills using tools such as Pandas, NumPy, Matplotlib, scikit-learn, and TensorFlow
• Apply your newly acquired skills across diverse professional contexts and data-related roles
• Use your completed practical projects to boost your professional portfolio and stand out in the job market

1. Python for Data Science Fundamentals
   1. Boolean Conditions
   2. Datetime and Random
   3. Loops and Strings
   4. Dictionaries
   5. NumPy
   6. Pandas DataFrames
   7. Bar Charts with Matplotlib
   8. Line & Scatter Charts with Matplotlib
   9. Pivot Population Data & Charts
   10. Basic Regression Analysis
   11. Introduction to Python and Colab/Jupyter Notebook setup for machine learning projects
   12. Load and explore car sales data using Pandas DataFrames
   13. Perform data slicing and initial statistical analysis: median, mode, standard deviation, variance, and percentiles
   14. Visualize uniform and normal distributions with Matplotlib
   15. Learn linear regression by modeling attendance vs. concessions
   16. Build prediction functions and apply user inputs
   17. Extend models with polynomial regressions
2. Supervised Learning Essentials
   1. K-Nearest Neighbors
   2. Titanic Survival Prediction
   3. Computer Vision: Convolutional Neural Networks (CNN) - Part 1: Grayscale Images
   4. Computer Vision: Convolutional Neural Networks (CNN) - Part 2: RGB (Color) Images
   5. Sentiment Analysis

Requirements:

Hardware Requirements:

• This course can be taken on either a PC or Mac. Chromebooks are not compatible.

Software Requirements:

• PC: Windows 10 or later.
• Mac: macOS 12 or later.
• Browser: The latest version of Google Chrome or Mozilla Firefox is preferred. Microsoft Edge and Safari are also compatible.
• Microsoft Word Online
• Adobe Acrobat Reader
• Google Colab
• Software must be installed and fully operational before the course begins.

Other:

• Email capabilities and access to a personal email account.

Instructional Material Requirements:

The instructional materials required for this course are included in enrollment and will be available online.

Prerequisites:

This course is for beginners. Students must be comfortable using a computer. No other prior knowledge is required.

Brian McClain

Brian McClain is a senior instructor and program director at Noble Desktop, where he teaches Python, data science, machine learning, and AI courses. His expertise covers several programming languages (including Python, R, and SwiftUI) and advanced frameworks (SQL, Flask, and OpenAI technologies). Brian holds certifications as a New York State Instructor of Computer Applications and a Licensed Private Career School Teacher. He earned his Bachelor's degree in Political Science from Duke University.

Colin Jaffe

Colin Jaffe is a programmer and curriculum developer at Noble Desktop. He has taught coding and software development at Noble Desktop as well as various other educational institutions. Colin's teaching focuses on algorithmic thinking, application logic, and practical frameworks such as React and Python. His professional background includes front-end development and data analytics, and he brings creativity to technical instruction, shaped by his experience as a self-taught programmer.

What is a data scientist?

A data scientist is a professional who uses data to solve problems and help organizations make better decisions. They collect, clean, and analyze large sets of data, often using tools like Python, R, SQL, and machine learning algorithms. Their work helps companies understand trends, predict future outcomes, and improve operations.

Data scientists often work in industries like technology, finance, healthcare, and retail. They need strong skills in statistics, programming, and communication to turn complex data into clear insights.

What is the average salary of a data scientist?

In 2025, the average salary for a data scientist in the United States is between $115,000 and \125,000 per year. Entry-level data scientists typically earn around $80,000 to $95,000, while those with a few years of experience make $105,000 to $130,000. Senior data scientists can earn $140,000 to $175,000 or more, especially in tech-focused cities.

What is the average salary of a Python developer?

In 2025, Python developers in the U.S. earn an average salary ranging from $82,000 to $117,000 per year. Beginners usually make $56,000 to $80,000, mid-level developers earn about $109,000 to $117,000, and senior Python developers can earn $130,000 or more, depending on their skills and the industry they work in.

What is a Python developer?

A Python developer is a programmer who writes software using the Python programming language. They may work in areas like web development, data analysis, automation, or artificial intelligence. Python developers often build websites, create tools for analyzing data, or develop machine learning models to solve complex problems.

Does this course prepare you for a certification?

No.

How long does it take to complete this course?

After you register, you will receive 9 months to complete the course. The time allotted for completion has been calculated based on the number of course hours.

When can I start this course?

This course is open enrollment, so you can register and start the course whenever you are ready. Access to your course can take 24-48 business hours.

What if I don't have enough time to complete the course within the time frame provided?

The time allotted for course completion has been calculated based on the number of course hours. However, if you are unable to complete the course, contact the student advising team to see what options you may have available to work out a suitable completion date. Please note that an extension fee may be charged.

What kind of support will I receive?

Our courses are designed to accommodate various learning preferences. Depending on the course structure, you may get different forms of support. Self-paced courses are designed to be user-friendly and independent, minimizing the need for external support. In courses with instructors, our direct platform support feature includes opportunities for questions, discussions, and remediation, with email and phone support available for select courses. Our student advising team is available to guide you on program requirements and administrative requests, but they do not provide assistance with course content. Our goal is to provide you with the necessary support for success, whether it's through self-paced exploration, direct communication, or guidance from our advising team.

What happens when I complete the course?

Upon successfully passing the final exam, you will be awarded a certificate of completion from the school or organization that you registered through.

Am I guaranteed a job?

ed2go courses will help you gain the skills you need to obtain an entry-level position in most cases. However, you should always research the job market in your area before enrolling.

Can I get financial assistance?

ed2go courses are non-credit, so they do not qualify for federal aid, FAFSA, and Pell Grant. In some states, vocational rehab or workforce development boards may provide funding to take our courses. Additionally, you may qualify for financial assistance if you meet certain requirements. Learn more about financial assistance.

How can I get more information about this course?

If you have questions that are not answered on our website, representatives are available via LIVE chat. You can also call us at 1-877-221-5151 during regular business hours to have your questions promptly answered. If you are visiting us during non-business hours, please send us a question using the "Contact Us."