Data Analysts Training Curriculum
Our comprehensive training program is designed to equip you with the skills and knowledge required to excel in data analysis. Here is a detailed curriculum of our training modules:
1. Introduction to Data Analytics
Overview:
- Importance of Data Analytics
- Roles and Responsibilities of a Data Analyst
- Data Analytics Process and Lifecycle
Topics:
- Data Collection
- Data Cleaning and Preparation
- Data Exploration
- Data Visualization
- Data Interpretation and Reporting
Duration: 1 Week
2. SQL for Data Analysis
Module 1: SQL Basics
- Introduction to SQL
- Understanding Databases and Tables
- Basic Queries: SELECT, FROM, WHERE
- Sorting and Filtering Data: ORDER BY, DISTINCT, LIMIT
Module 2: Intermediate SQL
- Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
- Subqueries and Nested Queries
- Aggregate Functions: COUNT, SUM, AVG, MIN, MAX
- Grouping Data: GROUP BY and HAVING
Module 3: Advanced SQL
- Window Functions: ROW_NUMBER, RANK, DENSE_RANK
- Common Table Expressions (CTEs)
- Indexing and Performance Optimization
- Stored Procedures and Triggers
Hands-on Activities:
- Query practice with real-world datasets
- Optimization exercises and performance tuning
Duration: 2 Weeks
3. Power BI
Module 1: Getting Started with Power BI
- Introduction to Power BI Interface
- Connecting to Data Sources
- Data Import and Transformation using Power Query
Module 2: Building Visualizations
- Creating Reports: Tables, Charts, Maps
- Designing Interactive Dashboards
- Custom Visualizations and Slicers
Module 3: Advanced Power BI
- Introduction to DAX (Data Analysis Expressions)
- Creating Calculated Columns and Measures
- Data Modeling and Relationships
- Power BI Service: Sharing and Collaboration
Hands-on Activities:
- Building comprehensive reports and dashboards
- Implementing advanced DAX calculations
Duration: 2 Weeks
4. Tableau
Module 1: Introduction to Tableau
- Getting Started with Tableau Interface
- Connecting to Various Data Sources
- Basic Visualizations: Bar Charts, Line Charts, Pie Charts
Module 2: Advanced Visualizations
- Creating Dashboards and Stories
- Working with Maps and Geographic Data
- Interactive Filters and Parameters
Module 3: Data Analysis with Tableau
- Calculations and Table Calculations
- Data Blending and Joining
- Performance Optimization and Best Practices
Hands-on Activities:
- Designing interactive dashboards
- Real-world case studies and data exploration
Duration: 2 Weeks
5. Excel for Data Analysis
Module 1: Excel Fundamentals
- Advanced Formulas and Functions: VLOOKUP, INDEX, MATCH
- Data Cleaning Techniques: Text to Columns, Find & Replace
Module 2: Data Analysis Tools
- Using PivotTables and PivotCharts
- Data Visualization: Conditional Formatting, Sparklines
- Data Analysis Add-ins: Solver, Analysis Toolpak
Module 3: Advanced Excel Techniques
- Creating Dynamic Dashboards
- Automation with Macros and VBA
- Working with Large Datasets and Performance Tips
Hands-on Activities:
- Developing complex formulas and data models
- Building dynamic dashboards and reports
Duration: 2 Weeks
6. Python for Data Analysis
Module 1: Python Basics
- Introduction to Python and Jupyter Notebooks
- Basic Programming Concepts: Variables, Data Types, Control Structures
Module 2: Data Manipulation with Pandas
- Data Structures: Series and DataFrames
- Data Cleaning and Preparation
- Data Merging and Grouping
Module 3: Data Visualization and Analysis
- Plotting with Matplotlib and Seaborn
- Statistical Analysis and Hypothesis Testing
- Introduction to Machine Learning with Scikit-Learn
Hands-on Activities:
- Data manipulation and visualization projects
- Implementing basic machine learning models
Duration: 3 Weeks
7. Capstone Project
Objective:
- Apply knowledge from all modules to a real-world project.
- Develop a complete data analysis solution including data collection, analysis, visualization, and reporting.
Deliverables:
- Project Report
- Interactive Dashboards and Visualizations
- Presentation of Findings
Duration: 2 Weeks
8. Certification and Continuous Learning
Certification:
- Complete a final assessment to earn your certification.
- Receive a detailed transcript of skills and knowledge.
Continuous Learning:
- Access to updated resources, webinars, and advanced courses.
- Opportunities for further specialization and professional development.
Total Duration: Approx. 14 Weeks