Data Analytics Course – Complete Overview

1. What is Data Analytics?

Data Analytics is the process of examining raw data to find useful insights, trends, and patterns that help in making better business decisions.
It combines statistics, programming, and business knowledge to convert data into meaningful information.

2. Why Learn Data Analytics?

• 🔹 High demand in IT, Banking, Finance, Marketing, Healthcare, E-commerce.

• 🔹 One of the fastest-growing job fields worldwide.

• 🔹 Helps organizations in decision-making, forecasting, and automation.

• 🔹 Attractive salary packages and global opportunities.

3. Eligibility Criteria

• Minimum: 12th pass / Diploma holder

• Best suited for: Graduates in BCA, BBA, B.Com, B.Sc, MBA, MCA, B.Tech etc.

• Basic computer knowledge required

4. Duration

• Diploma in Data Analytics → 6 months

• Professional Data Analytics Course → 12 months
  (Duration may vary depending on module depth & practice hours)

5. Course Modules

🔹 Module 1: Basics of Data Analytics

• Introduction to Data Analytics

• Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive

• Data Collection & Cleaning

• Understanding Business Problems

🔹 Module 2: Excel for Data Analysis

• Advanced Excel functions (VLOOKUP, HLOOKUP, Pivot Table, Power Query)

• Charts, Graphs, Dashboard creation

• Data Cleaning & Formatting

🔹 Module 3: Statistics & Mathematics for Data Analytics

• Probability & Sampling

• Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation)

• Hypothesis Testing & Correlation

• Regression Analysis

🔹 Module 4: SQL for Data Management

• Database concepts (RDBMS, Tables, Joins, Keys)

• Writing Queries

• Data Filtering, Aggregations, Subqueries

• Handling large datasets

🔹 Module 5: Data Visualization Tools

• Power BI – Reports, Dashboards, DAX Functions

• Tableau – Charts, Filters, Interactive Dashboards

• Google Data Studio

🔹 Module 6: Programming for Analytics

• Python Basics (Data types, loops, functions)

• Python Libraries: NumPy, Pandas, Matplotlib, Seaborn

• Data Cleaning & Manipulation with Pandas

• Exploratory Data Analysis

🔹 Module 7: Machine Learning (Introductory)

• Supervised & Unsupervised Learning

• Regression, Classification, Clustering

• Use of Scikit-learn

🔹 Module 8: Big Data (Basic)

• Introduction to Hadoop & Spark

• Handling large datasets

🔹 Module 9: Real-World Projects

• Sales Analysis

• Customer Segmentation

• Predictive Analytics for Business

• HR Analytics, Finance Analytics

6. Tools & Software Covered

• Excel (Advanced)

• SQL

• Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn)

• Tableau

• Power BI

• Google Analytics / Google Data Studio

• Basics of Hadoop / Spark

7. Career Opportunities

After completing the course, students can work as:

• Data Analyst

• Business Analyst

• MIS Executive

• Reporting Analyst

• Data Scientist (with further specialization)

• Research Analyst

• Market Analyst

8. Average Salary in India

• Freshers: ₹3 – 5 LPA

• Mid-level: ₹6 – 12 LPA

• Senior level: ₹15 – 25+ LPA

9. Industries Hiring Data Analysts

• IT Companies

• E-commerce & Retail (Amazon, Flipkart)

• Banking & Finance (HDFC, ICICI, SBI)

• Healthcare

• Marketing & Digital Advertising

• Government & NGOs

10. Certification

After successful completion, students will get:

• Course Completion Certificate

• Project-based Practical Certificate

• Internship Letter (if applicable)