LPU - Lovely Professional University
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
  • Introduction to Python, Jupyter Notebook setup, core programming concepts including variables, data types, control flow, OOP, and hands-on exploration of NumPy and Pandas.
  • Creating charts with Matplotlib and interactive visuals with Plotly, step-by-step dataset exploration, and understanding key statistics like mean, median, variance, and correlation.
  • Introduction to ML types and workflows, building models using Linear and Logistic Regression, Decision Trees, K-Means Clustering, and evaluating performance with accuracy, precision, and recall.
  • Understanding neurons and layers, building neural networks with Keras, applying transfer learning with pre-trained models, and an introduction to NLP and sentiment analysis.
  • Prompt engineering, building a RAG-based Q&A chatbot, developing a mini AI app using the Gemini API and Streamlit, responsible AI practices, and a final demo of each student's own AI-powered application.

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Arun Prakash K
Assistant Professor

Mr. Arun Prakash K brings the best of both worlds — 3 years of hands-on startup industry experience and 2 years of dynamic teaching — making his sessions as practical as they are insightful. A recognised AI Ambassador at LPU, he is deeply passionate about advancing AI literacy and empowering the next generation of tech innovators. His expertise spans Cloud Computing, Machine Learning, Artificial Intelligence, Data Structures & Algorithms, and programming languages including Python, C, and Java. With a strong command of Microsoft Azure and a knack for project-based learning, Mr. Arun Prakash brings real-world relevance to every concept he teaches — ensuring students don't just learn, but build.


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Dr. Shilpa Sharma
Professor

Meet Your Instructor – Dr. Shilpa Sharma With over 16 years of teaching and industry experience spanning Cloud Computing, Artificial Intelligence, Machine Learning, and Programming, Dr. Shilpa Sharma brings deep expertise and a passion for making complex technology accessible to every learner. Known for her practical, hands-on teaching approach, she has mentored hundreds of students and professionals, helping them bridge the gap between academic knowledge and real-world engineering skills. Whether you're writing your first line of code or deploying your first AI model, Dr. Sharma's structured guidance and industry insight will give you the confidence to build, innovate, and excel in the ever-evolving world of tech.