skilldevelopment.cpe@lpu.co.in

What you'll learn

Course Description: "CodeQuery: The Ultimate PL/SQL & Data Science Bootcamp" is a comprehensive 50-hour program designed to equip learners with essential PL/SQL programming skills and foundational data science knowledge. This bootcamp blends hands-on SQL & PL/SQL training with data science concepts, enabling participants to efficiently manage databases, optimize queries, and apply statistical and machine learning techniques to real-world problems. With a structured 4-week curriculum, daily interactive sessions, and practice-based learning, this course ensures practical expertise in database programming and analytics. Learning Outcomes: By the end of this course, participants will be able to: Master SQL & PL/SQL programming, including stored procedures, triggers, and performance optimization. Design and manage relational databases using normalization, indexing, and security best practices. Implement data preprocessing, exploratory data analysis (EDA), and statistical techniques for data insights. Apply foundational machine learning techniques, such as regression, classification, and clustering. Work with NoSQL databases, cloud data solutions, and deployment frameworks to handle real-world data challenges.

  • This module introduces relational databases, SQL vs. PL/SQL, and Oracle database architecture. It covers PL/SQL block structures, variables, data types, control structures, cursors, exception handling, and stored procedures.
  • Dive into advanced PL/SQL concepts like triggers, views, packages, and transaction management. Learn performance optimization techniques in PL/SQL and transition into data science fundamentals, including Python basics and key libraries like Pandas and NumPy.
  • Explore SQL for data extraction, data wrangling, and exploratory data analysis (EDA). Understand machine learning fundamentals, regression models, supervised learning (Decision Trees, SVM), and unsupervised learning (Clustering, K-Means).
  • Focus on feature engineering, model evaluation techniques, and predictive analytics using SQL and Python. Gain insights into optimizing machine learning models and improving performance through data-driven techniques.
  • Learn how to deploy machine learning models within databases and integrate them with real-world applications. Topics include Flask, FastAPI, and Streamlit for deployment, along with database-driven AI solutions.
  • Prepare for industry roles with resume building, LinkedIn optimization, and mock interviews. Explore the future of PL/SQL, AI-powered database management, and emerging trends in data science and database automation.

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Dr. Avinash Kaur
Professor

Dr. Avinash Kaur


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Dr. Parminder Singh
Professor & Dy. Dean

Dr. Parminder Singh