COURSE DESCRIPTION
Learn the core skills of Data Analytics including data handling, statistical analysis, data visualization, and machine learning basics. Gain practical knowledge using tools like Excel, SQL, Python, Tableau, and Power BI to drive data-driven decision-making.
SYLLABUS
What is Data Analytics?
Types of Data Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
Importance of Data in Modern Business
Real-World Applications of Data Analytics
Methods of Data Collection
Data Cleaning Techniques
Handling Missing Data
Introduction to Data Formats (CSV, JSON, XML
Basics of Statistics (Mean, Median, Mode, Standard Deviation)
Probability Theory
Hypothesis Testing
Correlation and Regression Analysis
Importance of Data Visualization
Best Practices for Effective Visualization
Creating Charts and Graphs
Using Tools: Tableau, Power BI, Excel Dashboards
Introduction to Databases
Writing Basic SQL Queries
Advanced SQL: Joins, Subqueries, Window Functions
Data Manipulation using SQL
Python Basics: Variables, Data Types, Control Structures
Libraries: Pandas, NumPy, Matplotlib, Seaborn
Data Cleaning and Preparation with Pandas
Exploratory Data Analysis (EDA) with Python
Introduction to BI Tools
Building Interactive Dashboards
Real-time Data Reporting
Case Study: Create a BI Report for a Business Scenario
What is Machine Learning?
Supervised vs Unsupervised Learning
Simple Predictive Modeling using Scikit-learn
Model Evaluation Metric
Sales Forecasting using Time Series Data
Customer Churn Analysis
Market Basket Analysis
Social Media Sentiment Analysis
Final Project Submission
Certification Exam
Career Guidance for Data Analysts
Excel
SQL
Python
Tableau
Power BI
Google Analytics (optional bonus)
Course Features
- Lectures : 20
- Quizzes : 5
- Max Student : 20
- Certificate : Yes
- Assessments : Yes
- Mock-up Interview : Yes
- Mode : Online & Offline
- Language : English, Hindi