Machine Learning Basics: Python, Numpy & Scikit-Learn
Learn core ML algorithms from scratch—linear regression, neural networks, and more—using real data and practical coding.
Machine Learning Basics: Python, Numpy & Scikit-Learn free download
Learn core ML algorithms from scratch—linear regression, neural networks, and more—using real data and practical coding.
Are you eager to break into the world of machine learning but overwhelmed by where to begin? This course offers a clear, hands-on, and structured path into the field, guiding you from foundational concepts to practical model building—without requiring any prior experience in machine learning.
In this course, you’ll not only understand how machine learning works, but also build your own models from scratch, code by code, using powerful tools like Python, Numpy, Pandas, Matplotlib, Scikit-learn, and Keras. You’ll go beyond the "plug-and-play" use of libraries to really grasp what’s happening under the hood—giving you confidence, depth, and true skill.
Tools & Frameworks You’ll Learn and Use
Python, Numpy, Pandas, Matplotlib, Seaborn
Scikit-learn and Keras
Google Colab (no setup required!)
RDKit for molecular analysis
DeepChem and MolGraph for advanced applications
What Makes This Course Different?
This is not a passive, lecture-only course. It’s a hands-on, problem-focused journey where you’ll:
Write algorithms manually before using libraries—so you understand the logic
Work with real datasets, including molecular chemistry and image recognition
Build regression and classification models using Python and Google Colab
Train and evaluate neural networks from scratch and using Keras
Apply advanced topics like regularization, batching, overfitting prevention, and graph convolution
Explore tools used in cutting-edge applications like drug discovery (RDKit and DeepChem)
You’ll learn not just how to use machine learning tools, but also how and why they work—empowering you to build your own solutions, not just replicate tutorials.
If you're serious about learning machine learning the right way—from intuition to implementation—this course will give you a solid foundation and practical skillset that you can apply immediately.
Join now, and start building real machine learning models with Python today.
