About the Program
The Data Science program is designed to help learners gain expertise in Python programming, data analysis, visualization, and machine learning. The course provides hands-on experience with real-world datasets and AI-driven projects to develop practical skills in predictive analytics and decision-making.
What You’ll Learn
- Python programming for data analysis
- Data manipulation using Pandas and NumPy
- Data visualization with Matplotlib and Seaborn
- Exploratory Data Analysis (EDA) techniques
- Machine Learning algorithms for prediction and classification
- SQL and Database Management
- Real-world AI and Data Science projects
Why Choose This Course?
- Learn from industry experts with real-time project experience
- Hands-on training with real datasets and assignments
- Comprehensive coverage of Python, Machine Learning, and AI concepts
- Placement assistance and career mentorship
- YVU–SkillDzire recognized certification
Who Can Join?
Ideal for beginners, students, and professionals who want to build a career in Data Science, Machine Learning, or AI-driven Analytics.
Course Curriculum
1. Introduction to AI & Data Science
- Justification of AI & Data Science
- Introduction to Data Science
- Machine Learning Concepts
2. Introduction to Python
- Python Important Features
- Interfaces or Software to Execute Python
- Python Basics
- Types of Operators in Python
- Control Statements in Python
- Functions in Python
- Packages & Modules in Python
- Exception Handling in Python
3. Python Data Structures
- Python Data Structures
- List Data Structures
- String Data Structure
- Sets and Tuples
- Dictionaries
- Files Concept in Python
- Regular Expressions
4. Object-Oriented Programming (OOP) in Python
- Object-Oriented Programming in Python
5. Data Analysis with Python
- Numpy Module
- Pandas Module
- Numpy Arrays
- Pandas Series Operations
- Pandas Aggregate Functions
- Pandas Aggregate Operations (Continued)
- Matplotlib Module
- Statistics
- Exploratory Data Analysis (EDA)
- EDA Continuation
6. SQL and Database Management
- Introduction to DBMS
- SQL Introduction
- SQL DB Creation
- SQL Concepts – SELECT, JOINS, WHERE CLAUSE
- SQL – CASE Statements
- SQL Ranking
7. Machine Learning with Python
- Simple Linear Regression
- Multiple Linear Regression
- Logistic Regression with Python
- Confusion Matrix, ROC Curve
- Naive Bayes ML Algorithm
- Hypothesis Testing for t-test
- Two Sample t-test
- Polynomial and Exponential Regression
8. Real-Time Tasks
- Exploring Wine Quality: A Data-driven Analysis and Classification Approach
- A Data-Driven Approach for Predicting Boston House Prices
- Stock Market Prediction and Forecasting: An Ensemble Learning Approach
- Analyzing and Predicting Movie Ratings: A Comprehensive Study on the IMDb Movie Dataset
- Identification and Analysis of Chronic Disease Indicators: A Data Science Perspective
- Analysis of Titanic Passengers Survived using Logistic Regression
- Analysis of Different Car CO2 Emission Models using Multiple Linear Regression
- Analysis of Sales Prices for TV Marketing using Simple Linear Regression
- Analysis of Bank Dataset Using Exploratory Data Analysis
Earn Your Certificate
On completion, you’ll receive an industry-recognized certificate from YVU – SkillDzire.
Real-Time Data Science Projects
Wine Quality Analysis
Analyze wine quality dataset using Python, perform data cleaning, exploratory data analysis (EDA), and predictive modeling.
Boston House Price Prediction
Build a machine learning model to predict house prices using regression techniques and visualize key factors affecting prices.
Stock Market Forecasting
Develop a predictive model using historical stock data, implement feature engineering, and forecast future stock prices.
Career Outcomes
Data Analyst
Salary Range: ₹3–6 LPA
Machine Learning Engineer
Salary Range: ₹4–8 LPA
Data Scientist
Salary Range: ₹5–12 LPA
What Our Students Say
“The Data Science program helped me gain practical skills in Python, SQL, and Machine Learning. I completed real-time projects on data analysis and soon after started working as a Data Analyst.”
– Riya, Infosys
“Hands-on projects with AI and predictive modeling made learning Data Science very effective. I now work as a Machine Learning Engineer and feel confident solving real-world data problems.”