What you'll learn

AIxCode is a hands-on, project-driven course crafted for B.Tech students eager to master Artificial Intelligence and Machine Learning from the ground up By the end of this course, students will be able to: 1. Write clean, efficient Python code using modern features: OOP, list comprehensions & modules. 2. Load, clean, and analyse real-world datasets using NumPy & Pandas. 3. Create insightful data visualisations with Matplotlib, Seaborn & Plotly. 4. Perform Exploratory Data Analysis (EDA) to extract meaningful patterns from data. 5. Build, train, and evaluate classical ML models: Regression, Decision Trees & K-Means. 6. Design and train neural networks using Keras & TensorFlow for classification tasks. 7. Apply Transfer Learning to solve real-world image classification problems. 8. Understand NLP fundamentals: tokenisation, embeddings & sentiment analysis. 9. Write effective prompts and build RAG-based chatbots using LangChain & Gemini API. 10. Deploy a working AI-powered mini-app using Streamlit and follow Responsible AI principles.

  • What is Python? Setup, Jupyter Notebook & Writing Your First Program Python Basics: Variables, Data Types, Lists & Simple Operations Control Flow: If/Else, Loops & Writing Simple Functions Intro to OOP: What are Classes & Objects? A Beginner-Friendly Walkthrough Intro to NumPy & Pandas: Loading a Dataset & Exploring It
  • Your First Charts: Line, Bar & Pie Charts with Matplotlib Reading Data Stories: How to Explore a Dataset Step by Step Understanding Numbers: Mean, Median, Variance & What Correlation Means Making Charts Interactive: Intro to Plotly with a Real Dataset Evaluation 1: Code Based Test
  • What is Machine Learning? Types, Real-World Uses & the ML Workflow Your First ML Model: Predicting with Linear & Logistic Regression How Decision Trees Work: A Visual, Intuitive Introduction Did My Model Work? Understanding Accuracy, Precision & Recall Finding Groups in Data: Intro to Clustering with K-Means
  • What is a Neural Network? Neurons, Layers & How They Learn Building Your First Neural Network with Keras (Step by Step) Transfer Learning: Using Pre-Trained Models Without Starting from Scratch Intro to NLP: How Computers Read Text & Understand Sentiment Evaluation 2: Code Based Test
  • What is Prompt Engineering? Writing Better Prompts for Better Answers What is a Chatbot & How Does RAG Work? Build a Simple Q&A Bot Using the Gemini API: Build a Mini AI App with Streamlit Responsible AI: Why Bias & Hallucinations Matter & How to Stay Safe Final Project: Build & Demo Your Own AI-Powered Mini App

Arun Prakash K
Assistant Professor

Arun Prakash K


Dr. Shilpa Sharma
Professor

Dr. Shilpa Sharma