Anand Group – Corporate Training Program

Anand Group (Anand Automotive Pvt. Ltd.) - Corporate Training Program

Industry Training Programs delivered to Anand Group Employees, covering AI, ML, Python, SQL, Data Analysis, and Data Visualization

Prakash Ukhalkar

About this Training

A structured, hands-on corporate training program delivered to employees of Anand Group (Anand Automotive Pvt. Ltd.), covering Data Analysis using Python and SQL across two progressive phases. Sessions were conducted using Jupyter Notebooks on Google Colab and VS Code, progressing from SQL-based database management to Python-powered data science and manufacturing quality analytics.

Training Objectives:

Create and manage relational databases using Python's built-in sqlite3 module
Write SQL queries - SELECT, WHERE, ORDER BY, GROUP BY, HAVING, JOIN, and Subqueries
Visualize business data (bar, pie, line, scatter, histogram) from live SQL results using Matplotlib
Perform array-based numerical computing & statistical summaries using NumPy
Load, clean, filter, & aggregate tabular data using Pandas DataFrames
Apply statistical visualization (heatmaps, pair plots, distribution charts) using Seaborn
Build end-to-end data pipelines from raw CSV/Excel data to visual reports
Apply Statistical Process Control (SPC) - X-bar, R, p-chart, c-chart, and Cpk to manufacturing quality data

Learning Outcomes:

Query, update, & manage SQLite databases using Python
Generate professional data visualizations from database & tabular data
Use NumPy & Pandas for data analysis and statistical summaries
Build a Manufacturing Quality Dashboard using SPC methods from Excel/CSV data
Execute complete batch quality analysis pipelines independently

Training Structure

Phase 01 - Python and SQL for Manufacturing

Covers SQLite3 database operations, SQL querying techniques (JOINs, GROUP BY, Subqueries), and Matplotlib-based data visualization directly from database query results culminating in a Capstone with a Manufacturing SPC Quality Dashboard.

SQLite3 SQL Querying Matplotlib SPC & Cpk Capstone

Jump to Phase 01

Presentations:

Phase 02 - Python for Data Analytics

Builds Python data science skills with NumPy, Pandas, Matplotlib, Seaborn, and SQLite3 integration ending with a lab assignment requiring a complete Batch Quality Analysis Pipeline from raw data to visual summary.

NumPy Pandas Seaborn SQLite3 Lab Assignment

Jump to Phase 02

Presentations:

Phase-02 Training Orientation Session - Python for Data Analytics

Tools & Environment:

Python 3.10+ SQLite3 Jupyter Notebooks Google Colab VS Code Excel CSV

Phase 01 - Python and SQL for Manufacturing

Hands-on sessions using Python's sqlite3 module to create and manage relational databases, write production-grade SQL queries, visualize query results with Matplotlib, and build a Manufacturing SPC Quality Dashboard as the capstone project.

Day 1: Employee & Department

Introduction to relational databases using Employee and Department tables.

Open Notebook

Day 2: SQL Querying

Advanced SQL querying techniques - filtering, joins, aggregations, and subqueries.

Open Notebook

Day 3: Data Visualization

Visualizing database outputs and business data using charting techniques.

Open Notebook

Day 4: Capstone Project

End-to-end capstone project integrating SQL querying and data analysis concepts.

Open Notebook

Day 4: Statistical Process Control

Introduction to SPC concepts and control charts for quality data analysis.

Open Notebook

SQL Practice Exercises

Curated SQL practice problems to reinforce querying skills learned across Phase 01.

Open Notebook

Phase 02 - Python for Data Analytics

Builds on Phase 01 by introducing the full Python data analytics stack - NumPy arrays, Pandas DataFrames, Matplotlib charts, Seaborn statistical plots, and SQLite3 integration — with a lab assignment requiring an end-to-end Batch Quality Analysis Pipeline.