LPU - Lovely Professional University
What you'll learn

Unlock the power of data analytics and automation in the Next-Gen Data Bootcamp. This hands-on course covers SQL, Power BI, Python, Machine Learning, and AI automation. Learn to write complex SQL queries, build interactive dashboards with Power BI, analyze data using Python, and implement machine learning algorithms. Gain the skills to automate data processes with AI and apply data-driven insights to solve real-world business challenges. By the end of the course, you’ll have a comprehensive skill set in data analytics, machine learning, and automation, preparing you for a successful career in the data-driven future.

  • Understanding Data Science & its Applications, Role of a Data Scientist & Industry Use Cases, Data Science Tools: Python, SQL, Power BI Introduction to SQL & Databases, Working with Relational Databases, Basic SQL Queries: SELECT, INSERT, UPDATE, DELETE, CONSTRAINTS in SQL Filtering & Aggregation: WHERE, GROUP BY, HAVING, ORDER BY + Leetcode Practice Joins & Subqueries: INNER JOIN, LEFT JOIN, RIGHT JOIN + Leetcode Practice Advanced SQL: Window Functions + Leetcode Practice
  • Introduction to PowerBI interface, Importing Data into Power BI, Data Cleaning Building and Structuring Data Models Advanced Calculations with DAX Designing and Enhancing Visual Reports Map Visuals: Using geographic data for map visuals, Adding slicers for filtering data, Filtering Options - TOP N filtering
  • 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) Matplotlib & Seaborn for Data Visualization : Case Study
  • 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
  • Introduction to Generative AI , Large Language Models LLM APIs, Prompt Engineering Agentic AI Building AI Agents Creating AI workflows using n8n Using MCP to create automated workflows

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Sandeep kaur
Assistant Professor

Passionate about Data Science and Data Analytics , I am an Assistant Professor and Mentor dedicated to fostering academic excellence and personal growth. With more than 7 years of experience in higher education, I have had the privilege of instructing and mentoring a diverse range of students in the field of Data Science and Web Development. Alongside my teaching, I also work on freelance projects, provide placement-oriented training sessions and mentor students to achieve their goals. My expertise extends to programming languages such as Python and R, data visualisation tools like Tableau and PowerBI, performing Data Analysis using Microsoft Excel. I am proficient in SQL for efficient data retrieval and manipulation,and have experience working with ETL tools such as SSIS and Informatica. Moreover, I have worked on Projects using Front-End Technologies like React/Angular. I actively engage in freelance projects, continuous professional development, attending industry conferences, participating in online courses, and contributing to data science communities.


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Savleen Kaur
Assistant Professor

Ms. Savleen Kaur is an Asst. Professor with 15+ years of experience in higher education, specializing in Artificial Intelligence, Natural Language Processing, and Data Science. She is dedicated to fostering academic excellence, innovation, and research-driven learning among students. With extensive expertise in AI, machine learning, and NLP, she integrates advanced concepts into her teaching while actively contributing to impactful research. Her work spans areas such as Gurmukhi to Shahmukhi transliteration, sarcasm detection, sentiment analysis, text-to-sign language translation, and COVID-19 contagion risk prediction, reflecting her commitment to solving real-world challenges through technology.Alongside her academic role, she mentors aspiring data scientists and AI professionals, guiding them in bridging the gap between theoretical knowledge and practical implementation. She actively engages in research collaborations, continuous professional development, and contributes to the data science community. Through her dedication to teaching, research, and mentorship, she continues to drive meaningful advancements in artificial intelligence and inspire the next generation of innovators.