๐ Data Science Course at Vagdevi Technologies, Ameerpet
๐๏ธ Duration: 16 Weeks (MondayโFriday, Daily Classes)
๐ง Mode: Offline & Online(Ameerpet)
๐ผ Includes:
Daily Theory + Practical Sessions
Weekly Assignments & Projects
Resume Preparation Support
Weekly Mock Interviews
๐ Course Structure
Python for Data Science
Introduction to Python, Jupyter Notebook, Basic Syntax
Data Structures (Lists, Tuples, Dictionaries, Sets)
Loops, Functions, File Handling
Numpy & Pandas Basics
๐น Mini Project: Data Cleaning using Pandas
Data Analysis and Visualization
Advanced Pandas, GroupBy, Merging, Pivot Tables
Data Visualization with Matplotlib
Visualization with Seaborn
Exploratory Data Analysis (EDA)
Real-Time Data Analysis (Case Study)
๐น Mini Project: EDA on Titanic / Sales Dataset
Statistics & Probability for Data Science
Descriptive Stats (Mean, Median, Mode, Variance)
Probability, Bayes Theorem, Distributions
Hypothesis Testing
Confidence Intervals, P-values
Real-Time Statistical Analysis
๐น Assignment: Statistical Report on Sample Data
Machine Learning – Supervised
Intro to ML, Workflow, Train-Test Split
Linear Regression
Logistic Regression
Decision Trees & Random Forest
Model Evaluation (Accuracy, Confusion Matrix, AUC)
๐น Mini Project: Predictive Modeling on Housing/HR Dataset
Machine Learning – Unsupervised
Clustering (K-Means, Hierarchical)
Dimensionality Reduction (PCA)
Market Basket Analysis (Apriori)
๐น Mini Project: Customer Segmentation
SQL and Big Data Basics
SQL for Data Science โ Select, Joins, Subqueries
Aggregate Functions, Window Functions
Intro to Big Data, Hadoop, Spark Overview
๐น Assignment: SQL Queries for Sales Data Analysis
Capstone Project + Resume + Mock Interviews
Capstone Project Work (End-to-End Pipeline)
Final Project Submission
Resume Building + LinkedIn Optimization
Group Mock Interviews:
1-on-1 Interview Practice Sessions
Bonus Modules & Industry Tools
Power BI / Tableau Introduction
Git & GitHub for Data Science
Deployment with Streamlit
Job Portal Guidance (Naukri, LinkedIn, etc.)
Outcomes:
Job-ready Data Science Portfolio
Polished Resume & LinkedIn Profile
Hands-on with ML Projects & Tools
Confidence for Real Interviews



