Learn Machine Learning in 2024

Are you curious about machine learning but don’t know where to start?

We just published a comprehensive Machine Learning course on the freeCodeCamp.org  that will teach you how to get started in 2024. Whether you’re aspiring to become a Data Scientist, a Machine Learning Engineer (MLE), a Product Manager, or a leader wanting to grasp the basics of ML, this course is a great starting point.

Tatev Aslanyan created this coruse. She is a seasoned data science professional with expertise in Machine Learning, Deep Learning, NLP, AI, and Statistical Modelling. She holds a Bachelor’s and Master’s degree in Econometrics and Operations Research from top-tier universities in the Netherlands.

What Makes This Course Stand Out?

Here are some of the key features in this course.

Machine Learning Roadmap for 2024 and Career Path: Kickstart your journey with a detailed roadmap crafted for 2024, guiding you through essential steps, portfolio projects, and career paths in machine learning. This course is designed to lay out a clear path for beginners, demystifying the field and highlighting opportunities within.

ML Theory Basics: Dive deep into the core concepts of machine learning, such as regression, classification, and evaluation metrics. Unlike other courses that skim the surface, we delve into these topics with the beginner in mind, ensuring a solid foundational understanding.

Practical Algorithms: Gain hands-on experience with linear and logistic regression, exploring their applications in causal analysis and predictive analytics. This course is structured to provide a practical understanding of both regression and classification algorithms at an entry-level.

End-to-End ML Project in Python: Apply what you’ve learned in a comprehensive project analyzing California house prices with Kaggle data. From data preprocessing to visualization and implementing linear regression, this section covers the A to Z of conducting an ML project, including how to enhance your model and showcase it on your resume.

Next Steps and Resources: We don’t just leave you at the end of the course. Detailed guidance on next steps, along with free resources, are provided to help you navigate through advanced topics and further your learning journey based on proven experience and research.

What Will You Learn?

You will learn about the follwoing topics, which are important if you are interested in machine learning.

• Introduction to Machine Learning: Understand the basics and the significance of machine learning in today’s world.
• Comprehensive Skill Set for a Career in ML: Learn what skills are crucial for a career in machine learning and how to acquire them.
• Exploring Career Paths: Discover common career paths in the field of machine learning.
• Understanding ML Basics: Get to grips with fundamental concepts like the bias-variance trade-off, overfitting, and regularization.
• Deep Dive into Algorithms: Explore the statistical version of linear regression, the theory behind logistic regression models, and more.
• Practical Application: Conduct a case study with linear regression, including data cleaning, preprocessing, descriptive statistics, outlier detection, and correlation analysis.
• Final Project: Undertake an end-to-end machine learning project using Python, from loading and exploring data to running linear regression for causal analysis and predictive analytics.

Conclusion

The goal of this course is to provide a valuable resource for beginners stepping into the world of machine learning. Watch the full course on the freeCodeCamp.org YouTube channel (4.5-hour watch).