Certificate Program on Basics of Artificial Intelligence and Machine Learning

Course Objective To introduce students to the fundamentals of Artificial Intelligence and Machine Learning, including key concepts, techniques, and tools used to build intelligent systems and datadriven models.

Course Instructor: Aman Jha

FREE

Course Overview

Key Learning Outcomes
By the end of the course, learners should be able to:
 Understand the difference between AI, ML, and Deep Learning.
 Identify different types of ML (supervised, unsupervised, reinforcement).
 Apply basic ML algorithms to real-world problems.
 Work with datasets: clean, preprocess, and visualize data.
 Use beginner-friendly tools like Python (scikit-learn), Jupyter Notebook, and Google
Colab.
 Evaluate and interpret ML model performance.
Who is it for?
 Students and professionals new to AI/ML
 Business analysts or developers exploring data science
 Anyone interested in understanding intelligent systems and data modeling
Duration 30 hours

Schedule of Classes

Course Curriculum

9 Subjects

AI Fundamentals

Search Algorithms (DFS, BFS)

Intelligent Agents

Python for AI/ML

Data Preprocessing

Mathematics for ML

Probability, Statistics

Machine Learning Basics

Unsupervised Learning (Clustering, PCA)

Model Evaluation (Accuracy, Precision, Recall)

Deep Learning

Frameworks: TensorFlow, PyTorch

Natural Language Processing (NLP)

Chatbots, Transformers

Reinforcement Learning

Q-Learning

AI Ethics & Deployment

Model Deployment (Flask, Streamlit)

Capstone Project

Image Recognition

Voice Assistants

Tools/Tech: Python, TensorFlow, PyTorch, Keras, Scikit-learn, OpenCV

Course Instructor

Aman Jha

26 Courses