SOFTWARE TRAINING

Class 9: SQL Basics – SELECT, FROM, WHERE, ORDER BY, LIMIT

Class 10: Aggregate Functions (COUNT, SUM, AVG, MIN, MAX), GROUP BY, HAVING Clause

Class 11: Data Manipulation Language (DML) - INSERT, UPDATE, DELETE. JOIN Operations (INNER, LEFT, RIGHT, FULL OUTER)

Class 12: Subqueries, Common Table Expressions (CTEs), CASE WHEN statements, Introduction to Window Functions

Class 13: Introduction to Power BI Desktop, Data Import from various sources, Interface Tour

Class 14: Data Transformation & Cleaning in Power Query Editor (ETL Process)

Class 15: Basic Visualizations (Bar, Pie, Line, Area, Card, Map) and Custom Visuals

Class 16: Data Modeling, Relationships between tables, Introduction to DAX (Data Analysis Expressions) Basics (SUM, CALCULATE, IF)

Class 17: Advanced DAX Functions and Time Intelligence

Class 18: Building Interactive Dashboards, Key Performance Indicators (KPIs), Slicers & Filters

Class 19: Row-Level Security, Incremental Refresh, and Report Performance Optimization

Class 20: Publish & Share Reports to Power BI Service + Power BI Mini Project

Class 1: Excel Basics, Interface, Data Entry & Formatting

Class 2: Essential Formulas (SUM, AVERAGE, COUNT, IF) & Logical Operations

Class 3: Text Functions (LEFT, RIGHT, MID, CONCATENATE), Date & Time Functions

Class 4: Advanced Data Cleaning Techniques & Conditional Formatting

Class 5: Lookup Functions (VLOOKUP, HLOOKUP, INDEX-MATCH) & Data Validation

Class 6: Pivot Table for Aggregation & Analysis, Pivot Chart for Visualization

Class 7: Data Grouping & Filtering, What-If Analysis (Goal Seek, Scenario Manager)

Class 8: Excel Dashboard Project (Mini Project) - Creating Interactive Dashboards

📗 Module 2: SQL for Data Analysts (সর্বনিম্ন ৪টি ক্লাস)

📙 Module 3: Power BI (সর্বনিম্ন ৮টি ক্লাস)

🐍 Module 4: Python for Data Analysis (সর্বনিম্ন ৪টি ক্লাস)

🧠 Module 5: Job-Ready Skills (Soft Skills) (সর্বনিম্ন ২টি ক্লাস)

🧪 Module 6: Capstone Project + Career Prep (সর্বনিম্ন ২টি ক্লাস)

কোর্সে যা থাকছে:

✔️ 3 Mini Projects 

Class 21: Python Basics – Variables, Data Types (Strings, Numbers, Booleans), Lists, Tuples, Dictionaries

Class 22: Introduction to pandas for Data Reading (CSV, Excel), Data Cleaning (Missing Values, Duplicates), Data Filtering & Selection

Class 23: Data Aggregation (groupby), Merging & Concatenating DataFrames, Reshaping Data (pivot, melt)

Class 24: Data Visualization with matplotlib & seaborn (Histograms, Scatter Plots, Box Plots, Bar Charts) + Mini Project

Class 25: Communication & Data Storytelling

Effective Slide Design for Data Reports

Presenting Insights to Technical & Non-Technical Audiences

Crafting a Compelling Data Narrative

Class 26: Critical Thinking & Problem Solving in Analytics

Translating Business Questions into Data Problems

Analytical Problem-Solving Frameworks

Interview Scenario–Based Challenges & Case Studies

• Class 27: Capstone Project Day

  • Working with a Real-Life, End-to-End Dataset

  • Applying Full Pipeline: Excel/SQL → Power BI/Python → Presentation

  • Project Documentation & Best Practices

• Class 28: Career Readiness

  • Optimizing Your Resume for Data Analyst Roles

  • Building a Strong Portfolio (GitHub/Google Drive/Personal Website)

  • Interview Preparation Q&A + Mock Interview Sessions