Machine Learning Fundamentals: Learn Core ML Concepts from Scratch

Machine Learning Fundamentals

A structured course designed to introduce learners to the core concepts, algorithms, and real-world applications of Machine Learning.

Course Overview

This course provides a detailed introduction to Machine Learning (ML), covering fundamental concepts, key algorithms, and real-world applications. Participants will learn about supervised and unsupervised learning, model evaluation, and optimization techniques. The course also covers popular ML libraries, data preprocessing, and feature engineering. By the end, learners will have the skills needed to build and deploy ML models.

FAQ

No. This is a beginner-friendly course that introduces all core concepts from scratch.

Yes. The course covers both the intuition behind algorithms and how to apply them in code.

Projects may include spam detection, house price prediction, and customer churn analysis.

Yes. It builds a strong foundation for more advanced topics like deep learning or NLP.

Course curriculum

Machine Learning -Quiz
0:10:0

Requirment

Basic Python programming skills
High school-level math (linear algebra, statistics)
Interest in data analysis and AI
Laptop with Python and libraries like Scikit-learn installed (or use Google Colab)

Outcomes

Understand core ML concepts: supervised, unsupervised, and basic reinforcement learning
Preprocess and analyze datasets for training and evaluation
Evaluate models using metrics like accuracy, precision, recall, and confusion matrix
Apply ML to real-world problems with hands-on projects

₹3499

~~₹4999~~

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language
English
Duration
00h 10m
Level
beginner
Expiry period
Lifetime
Certificate
Yes