CERTIFICATE IN DATA SCIENCE ( S-DATA SCIENCE )

Data Science – 2 Months Certification Course

Course Duration: 2 Months
Mode: (Theory + Practical)
Level: Beginner to Intermediate
Prerequisites: Basic Computer Knowledge

Unit 1: Introduction to Data Science

• What is Data Science?
• Key Terminologies
• Data Science Lifecycle / Process
• Introduction to Data Science Tools & Toolkit
• Types of Data: Structured, Semi-structured, and Unstructured

Unit 2: Data Collection Techniques

• Overview of Data Collection
• Types & Sources of Data
• Web Scraping Basics
• API Integration using Postman and Python (Requests)
• Cleaning Raw Data: Missing, Noisy, and Duplicate Data Handling

Unit 3: Data Analysis Essentials

• Fundamentals of Data Analysis
• Features, Observations, and Variables
• Exploratory Data Analysis (EDA)
• Data Summarization Techniques
• Tools Used: Pandas, NumPy (Basics)

Unit 4: Basic Statistics for Data Science

• Central Tendencies: Mean, Median, Mode
• Dispersion: Range, Variance, Standard Deviation
• Probability Distributions: Normal, Binomial, etc.
• Introduction to Visualization: Histograms & Boxplots

Unit 5: Sampling & Distribution Concepts

• Sampling Techniques: Random, Stratified, Systematic
• Law of Large Numbers
• Central Limit Theorem (CLT)
• Arithmetic on Probability Distributions

Unit 6: Introduction to Machine Learning

• What is Machine Learning?
• Categories: Supervised vs Unsupervised
• Linear Regression: Concept + Python Implementation
• Support Vector Machines (SVM) – Basics

Unit 7: Data Visualization Techniques

• Why Visualization Matters
• Chart Types: Line, Bar, Pie, Histogram, Heatmap
• Visual Encoding: Shape, Size, Color, Position
• Python Libraries: Matplotlib, Seaborn

Unit 8: Applications & Interactive Visualization Tools

• Real-life Applications of Data Science
• Introduction to Bokeh Library (Python)
• Interactive Dashboards
• Capstone Mini Project: From Data Analysis to Visualization

Course Highlights

• Hands-on Practical Sessions
• Real Dataset Case Studies
• Tools Used: Python, Pandas, NumPy, Matplotlib, Seaborn, Bokeh
• Certificate on Completion

Eligibility :- 12 PASS