Programming with Python

Master Python programming essentials for data analytics!

Join our student-friendly course and explore data manipulation, algorithms, visualization, libraries, and automation.

Introduction to Python

1. Variables, Expressions, and Statements

2. Functions, Iterations, Strings

3. Conditionals and Loops

4. Lists, Dictionaries, Tuples

5. Files Handling & Operations

6. Object-Oriented Programming (OOP)

7. Error and Exception Handling

Detailed Syllabus

Python for Data Analytics

1. Data Visualization

2. Data Manipulation with NumPy

3. Data Analysis with Pandas

4. Matplotlib & Seaborn

Learning SQL

Unlock the power of SQL for data analytics! Enroll in our course and gain essential skills in data querying, database management, data manipulation, aggregation, and modeling. Join us now to unleash the full potential of SQL in the realm of data analytics!

Introduction to MySQL

1. MySQL Installation

2. Getting Started with SQL and Queries

3. Queries with Constraints

4. DDL Statements, DML Statements

Module 1: Introduction to Databases and SQL

1. Introduction to Databases

· Definition of databases

· Types of databases: relational, NoSQL

· Overview of SQL as a query language

2. Relational Database Management Systems (RDBMS)

· Explanation of RDBMS concepts

· Popular RDBMS systems: MySQL, PostgreSQL, SQLite, Microsoft SQL Server, Oracle

3. SQL Basics

· Understanding SQL syntax

· Creating databases and tables

· Inserting, updating, and deleting data

· Retrieving data using SELECT statements

Module 2: Data Retrieval with SQL

4. Filtering and Sorting Data

· WHERE clause for filtering

· ORDER BY clause for sorting

5. Advanced Queries

· Joins (INNER, LEFT, RIGHT, FULL)

· Subqueries for nested queries

· UNION and UNION ALL

6. Aggregation Functions

· SUM, AVG, MIN, MAX, COUNT

· GROUP BY clause

Module 3: Data Manipulation with SQL

7. Data Modification

· Updating and deleting records

· Transactions and ACID properties

8. Views and Indexes

· Creating and using views

· Indexing for performance optimization

9. Stored Procedures and Functions

· Creating and executing stored procedures

· User-defined functions

Module 4: Advanced SQL Topics

10. Window Functions

· ROW_NUMBER(), RANK(), DENSE_RANK(), etc.

· OVER() clause

11. Analytical Functions

· LEAD, LAG, FIRST_VALUE, LAST_VALUE

· Percentile functions

12. Temporal Data and Time Series Analysis

· Working with date and time data

· Analyzing time series data using SQL

Module 5: SQL for Data Analytics

13. Data Aggregation and Reporting

· Creating summary reports

· Using GROUP BY and HAVING clauses

14. Data Cleaning and Transformation

· Handling missing data

· Data normalization and denormalization

15. Case Studies and Real-world Applications

· Applying SQL to real-world data analytics scenarios

· Troubleshooting and optimizing SQL queries

Module 6: Performance Optimization and Best Practices

16. Query Optimization Techniques

· Execution plans

· Index optimization

17. Best Practices in SQL

· Coding standards

· Security considerations

Module 7: NoSQL Databases and SQL Integration

18. Introduction to NoSQL Databases

· Overview of popular NoSQL databases

· Contrasting SQL and NoSQL

19. SQL and NoSQL Integration

· SQL access to NoSQL databases

· Data migration between SQL and NoSQL

Module 8: Final Project and Assessment

20. Capstone Project

· Implementing a data analytics project using SQL

· Presentation and documentation of the project

21. Assessment and Certification

· Final exam or project evaluation

· Awarding certificates

Introduction to Excel

1. Overview of Excel

· Introduction to Microsoft Excel

· Understanding the Excel interface

· Basic navigation and terminology

2. Data Entry and Formatting

· Entering data into cells

· Formatting text and numbers

· Using cell styles and themes

3. Cell Referencing and Formulas

· Understanding cell references (relative, absolute, mixed)

· Basic mathematical operations

· Common Excel formulas (SUM, AVERAGE, COUNT, etc.)

Module 2: Data Analysis and Visualization

4. Sorting and Filtering Data

· Sorting data in Excel

· Filtering data using AutoFilter

· Advanced filtering options

5. Data Visualization with Charts

· Creating charts (bar, line, pie, etc.)

· Customizing chart elements

· Using Sparklines for mini-charts

6. Conditional Formatting

· Highlighting cells based on conditions

· Data bars, color scales, and icon sets

· Managing rules and formats

Module 3: Advanced Excel Formulas

7. Advanced Mathematical and Statistical Formulas

· Statistical functions (AVERAGEIF, COUNTIF, SUMIF)

· Advanced mathematical functions (IFERROR, VLOOKUP, HLOOKUP)

8. Text Functions

· CONCATENATE, LEFT, RIGHT, MID

· Using TEXT functions for formatting

9. Date and Time Functions

· Working with dates and times

· Date calculations and formatting

Module 4: PivotTables and PivotCharts

10. Introduction to PivotTables

· Creating PivotTables

· Filtering and sorting PivotTable data

· Updating data source

11. PivotTable Calculations

· Adding calculated fields and items

· Creating custom calculations

· Grouping and ungrouping data in a PivotTable

12. PivotCharts and Dashboard Creation

· Creating PivotCharts from PivotTables

· Designing dashboards with Excel components

Module 5: Data Import and Export

13. Importing Data into Excel

· Importing data from external sources (CSV, Text, Database)

· Using Power Query for data import

14. Exporting Data from Excel

· Exporting data to different formats (CSV, PDF)

· Sharing and collaborating on Excel files

Module 6: Advanced Data Analysis Techniques

15. Scenario Manager and What-If Analysis

· Creating and managing scenarios

· Performing What-If Analysis with Data Tables

16. Solver Tool

· Introduction to Solver for optimization problems

· Setting up and solving optimization models

Module 7: Excel Automation with Macros

17. Introduction to Macros

· Recording and running macros

· Editing and debugging macros

· Introduction to VBA (Visual Basic for Applications)

18. Automating Tasks with VBA

· Creating custom functions and procedures

· Using loops and conditions in VBA

· Form controls and user forms

Module 8: Final Project and Assessment

19. Capstone Project

· Applying Excel skills to a real-world data analytics project

· Presentation and documentation of the project

20. Assessment and Certification

· Final exam or project evaluation

· Awarding certificates

Power BI

Elevate your data analytics expertise with Power BI! Enroll in our course to unleash the power of dynamic dashboards, stunning visualizations, and actionable reports. Master the art of transforming data into insights and making data-driven decisions. Join us now to become a Power BI wizard in data analytics!

Module 1

1. Introduction to Power BI

2. Data Cleaning in Power Query Editor

3. Menu Tabs in Power Query Editor

4. Advance Function in Power Query Editor

Module 2

1. Introduction to Power BI Desktop

2. Power BI Desktop Menu Tab

3. Measures in Power BI

4. Insert Menu

5. Data Visualization

Module 3

1. Charts, Maps, Tables & Its Types

2. Introduction to DAX Function

3. DAX and Measures

4. Basics of M Language & Bookmark

Module 4

1. Create a Dashboard

2. Create Filters on Dashboard

3. Dashboard Objects

4. Create a Story

Data Analytics Syllabus