Miit Computer education

Facebook Whatsapp Youtube Instagram
  • 93985 34916
  • miitcomputereducations@gmail.com
  • Hayathnagar,Hyderabad
miit
Contact Now

Data Science & Data Analytics

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

.

Data Science & Data Analytics is one of the most valuable technology courses for students, graduates, and working professionals who want to build a career in data-driven industries.

This course teaches students how to collect, clean, analyze, visualize, and interpret data using industry-relevant tools such as Python, SQL, Excel, Power BI, and Machine Learning.

 Course Overview

  • Course Name: Data Science & Data Analytics

  • Course Level: Beginner to Advanced

  • Duration: 4–6 Months (Suggested)

  • Mode: Classroom / Online

  • Eligibility: Any Degree / B.Tech / B.Com / B.Sc / MBA / MCA

  • Programming Language: Python

  • Career Focus: Data Analyst, Data Scientist, Business Analyst

Complete Course Syllabus

Module 1

Excel for Data Analytics

  • Excel fundamentals and advanced formulas

  • VLOOKUP, XLOOKUP, INDEX, MATCH

  • SUMIFS, COUNTIFS, IF functions

  • Pivot Tables and Pivot Charts

  • Data cleaning and dashboard creation

 
Module 2

SQL for Data Analysis

  • Introduction to databases

  • SELECT, WHERE, ORDER BY

  • GROUP BY and HAVING

  • Joins: INNER, LEFT, RIGHT

  • Subqueries and CTEs

  • Window Functions

  • Real-time SQL projects

 
Module 3

Python Programming

  • Python fundamentals

  • Variables, data types, operators

  • Conditional statements and loops

  • Functions and data structures

  • File handling

  • NumPy

  • Pandas

  • Matplotlib and Seaborn

 
Module 4

Power BI & Data Visualization

  • Power BI Desktop

  • Data import and transformation

  • Power Query

  • Data modeling

  • DAX formulas

  • Interactive dashboards

  • Business Intelligence reports

 
Module 5

Statistics for Data Science

  • Mean, Median, Mode

  • Variance and Standard Deviation

  • Probability

  • Correlation and Regression

  • Hypothesis Testing

  • Statistical Analysis

 
Module 6

Machine Learning

  • Introduction to Machine Learning

  • Supervised and Unsupervised Learning

  • Linear Regression

  • Logistic Regression

  • Decision Trees

  • Random Forest

  • K-Means Clustering

  • Model Evaluation

 
Module 7

Generative AI for Data Analytics

  • Introduction to Generative AI

  • Using AI tools for data analysis

  • AI-assisted Python programming

  • Automated reporting

  • AI-powered data insights

 Data Science vs Data Analytics

Data Analytics

Data Science

Analyzes historical data

Builds predictive models

Focuses on business insights

Focuses on predictions and patterns

Excel, SQL, Power BI

Python, SQL, ML

Data Analyst

Data Scientist

Beginner-friendly

Requires stronger programming and statistics

Which one should students learn first?

For beginners, Data Analytics is generally a good starting point. Students can then progress to Data Science and Machine Learning.

 Career Opportunities

Data Analyst

Analyzes business data and creates reports.

Business Analyst

Identifies business requirements and insights.

Data Scientist

Develops statistical and machine learning models.

Power BI Developer

Builds interactive business dashboards.

 Practical Projects

Students should complete the following projects during training:

  1. Sales Data Analysis using Excel

  2. SQL-Based Customer Data Analysis

  3. Python Data Cleaning and Analysis

  4. Power BI Sales Dashboard

  5. Customer Segmentation using Machine Learning

  6. Employee Attrition Prediction

  7. Real-Time Business Intelligence Project

 Course Description for Training Institute Website

Here is professional content you can use on your software training institute website.