LPU - Lovely Professional University
What you'll learn

This program is designed to transform students from campus learners into industry-ready Data & AI Engineers. You’ll start with strong foundations in SQL and Python, then progress into data analysis, machine learning, and real-world AI applications. Unlike traditional courses, this program focuses on hands-on projects, real datasets, and industry use cases so you can confidently step into corporate roles. By the end of the program, you won’t just know concepts—you’ll have built portfolio-ready projects, solved real business problems, and gained the skills recruiters actually look for. Learning Outcomes include • Write efficient queries using SQL for data extraction and analysis • Build strong programming logic using Python • Perform data cleaning, preprocessing, and exploratory data analysis (EDA) • Implement machine learning models for prediction and classification • Understand and apply core AI concepts in real-world scenarios • Work with popular libraries like Pandas, NumPy, Scikit-learn

  • Introduction to SQL & Databases, Working with Relational Databases, Creation of tables with constraints and Keys Basic SQL Queries: SELECT, INSERT, UPDATE, DELETE, Filtering & Aggregation: WHERE, GROUP BY, HAVING, ORDER BY Joins INNER JOIN, LEFT JOIN, RIGHT JOIN
  • SubQueries: Single Row Subquery, Multiple Row Subqueries Pattern Matching in Data using SQL Advanced SQL: Window Functions Normalization 1NF,2NF, 3NF,BCNF, 4NF and 5NF Introduction to PLSQL
  • Python Fundamentals : Data Types, Lists, Tuples, Dictionaries, Loops NumPy for Numerical Computing : Creating & Manipulating Arrays, Mathematical & Statistical Operations, Data Cleaning Pandas for Data Manipulation, Loading & Cleaning Data (Handling Missing Values) Data Transformation & Feature Engineering, Merging, Filtering, and Grouping Data Matplotlib & Seaborn for Data Visualization
  • Introduction to Machine Learning, Supervised vs. Unsupervised Learning, Overview of Libraries like Scikit-Learn, TensorFlow, Keras Regression & Classification Models, Linear Regression & Multiple Regression Logistic Regression Decision Trees Model Evaluation: RMSE, R², Confusion Matrix, Precision, Recall
  • Un-Supervised Learning:K-Means Clustering Principal Components Analysis (PCA) Model Persistence and Evaluation, Building a model for prediction Building & Deploying ML Models - Hyperparameter Tuning Final Project
  • Foundations of AI for Engineers Prompt Engineering Mastery Vibe Coding with AI Building & Deploying WebApplications Final Project

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Jaffar Amin Chacket
Assistant Professor

Jaffar Amin Chacket is an assistant professor at Lovely Professional University and a Roman Tech–certified Software Developer with a strong foundation in modern technologies. He brings extensive expertise in SQL, Python, Machine Learning, and Artificial Intelligence, along with hands-on experience from delivering advanced AI Mastery programs. Known for his practical approach to teaching, he effectively bridges theoretical concepts with real-world applications, empowering learners to build industry-relevant skills and stay ahead in the rapidly evolving tech landscape.