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
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
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