Tools: Excel → SQL → Python → Power BI → Artificial Intelligence (AI) → Soft Skills
Goal: Train participants to become confident in data preparation, extraction, analysis, and visualization.
MONTH 1 — Excel for Data Analytics (Foundation)
Week 1
Session1: Introduction to Data Analytics and Basics of Excel
- Introduction to Data Analytics
- Different tools used for Data Analytics
- Basics of Excel for Data Analytics
Session 2: Excel Basics & Interface
- Ribbon, menus, workbook vs worksheet
- Data entry, copy/cut/paste, autofill
- Freeze panes, basic shortcuts
- Hands-on: Structure a raw messy dataset
Session 3: Excel Formatting & Data Preparation
- Formatting cells, rows, columns
- Number, date, currency formats
- Conditional formatting, data validation
- Hands-on: Prepare a clean formatted dataset
Week 2
Session 4: Excel Formulas & Functions I
- SUM, AVERAGE, MIN, MAX, COUNT
- Logical functions: IF, AND, OR
- Date functions
- Hands-on: Calculate KPIs
Session 5: Excel Functions II & Lookups
- XLOOKUP / VLOOKUP
- Text functions: LEFT, RIGHT, MID, TRIM, CONCAT
- Relative vs absolute references
- Hands-on: Clean and enrich data
Session 6: Tables & Pivot Tables
- Tables vs ranges, sorting, filtering
- Pivot Tables & basic Pivot Charts
- Hands-on: Build a pivot report
Week 3
Session 7: Excel Practical Mini Project
- Clean, analyze, and summarize a business dataset
- Mini presentation of insights
Session 8: Communication as a Career Skill for Data Analysts
- Role of communication in a data analyst’s career
- Why insights fail without clarity
- Thinking clearly before speaking
- Communicating value, not effort
- Adapting communication for different audiences
- Handling questions and misunderstandings professionally
Session 9: Career Positioning & Industry Awareness
- Analyst roles across industries
- Understanding where data analysts fit in organizations
- Entry-level vs growth roles
- Aligning skills with industry needs
Week 4
SQL for Data Analytics
Session 10: Introduction to Databases & SQL Basics
- Relational database concepts
- Tables, keys, data types
- CREATE TABLE, INSERT INTO
- Hands-on: Set up a sample database
Session 11: SELECT Queries & Filtering
- SELECT, DISTINCT
- WHERE, BETWEEN, IN, LIKE
- ORDER BY, LIMIT/OFFSET
- Hands-on: Query business data
Session 12: Aggregations & Grouping
- COUNT, SUM, AVG, MIN, MAX
- GROUP BY, HAVING
- Hands-on: Summarize metrics
Week 5
Break: 11th & 12th
Week 6
Session 13: Joins & Relationships
- INNER, LEFT, RIGHT joins
- Joining multiple tables
- Hands-on: Combine datasets
Session 14: Subqueries & CTEs
- Subqueries in SELECT & WHERE
- Common Table Expressions (WITH)
- Hands-on: Prepare analytical datasets
Session 15: SQL Practical Project
- End-to-end SQL case study
- Build dataset for Python & Power BI
- Hands-on: Analytical reporting
Week 7
Session 16: Problem-Solving & Critical Thinking in Teams
- How analysts approach unclear problems
- Breaking down complex business questions
- Asking better questions
- Decision-making with incomplete information
- Emotional intelligence in problem-solving
- Working through mistakes and uncertainty
Python for Data Analysis & Statistics
Session 17: Python Basics for Data Analysis
• Basics of python programming
• Python IDE Jupyter/Colab environment
• Variables, data types, lists, dictionaries
• Reading CSV/Excel files
• Hands-on: Load dataset
Session 18: NumPy & Pandas Foundations
• NumPy arrays
• Pandas Series & DataFrames
• Indexing and selection
• Hands-on: Explore data
Week 8
Session 19: Data Cleaning with Pandas
• Handling missing values
• Removing duplicates
• Data type conversions
• Hands-on: Clean raw dataset
Session 20: Data Transformation & Feature Engineering
- Filtering & sorting
- groupby & aggregations
- Creating new features, merging datasets
- Hands-on: Transform data
Session 21: Exploratory Data Analysis (EDA)
- info(), describe()
- Correlation analysis
- Distribution & outlier detection
- Hands-on: EDA notebook
Week 9
Session 22: Data Visualization in Python
- Matplotlib & Seaborn
- Histograms, boxplots, scatter plots
- Hands-on: Visual EDA
Session 23: Descriptive Statistics -8/04/2026
• Mean, median, variance, standard deviation
• Skewness & normal distribution
• Hands-on: Interpret statistics
Session 24: Inferential Statistics
• Sampling & Central Limit Theorem
• Confidence intervals
• Hands-on: Simulations
Week 10
Session 25: Hypothesis Testing & Correlation
• t-test, chi-square test
• Correlation vs causation
• Hands-on: Tests in Python
Session 26: Python & SQL Integration
• Reading SQL data into Pandas
• Writing results back
• Hands-on: End-to-end workflow
Session 27: Python Analytics Mini Project (Build)
• Analyze dataset using Pandas & visuals
• Generate insights
Week 11
Session 28: Python & SQL Integration
• Reading SQL data into Pandas
• Writing results back
• Hands-on: End-to-end workflow
Session 29: Python Analytics Mini Project (Build)
• Analyze dataset using Pandas & visuals
• Generate insights
Session 30: Python Mini Project (Presentation)
• Notebook presentation
• Review & feedback
Week 12
Session 31: Personal Branding for Data Analysts
• What personal branding really means
• Building credibility without noise
• Online vs offline professional presence
• Consistency in communication and behavior
• Positioning expertise authentically
• Long-term reputation building
Introduction to Machine Learning
Session 32: ML Concepts for Analysts
- What is ML? Business use cases
- Supervised vs unsupervised learning
- ML workflow
- Hands-on: Simple example
Session 33: Regression for Prediction
- Linear regression with scikit-learn
- Metrics: MAE, RMSE, R²
- Hands-on: Sales/price prediction
Week 13
Session 34: Classification for Decisions
- Logistic regression
- Metrics: accuracy, precision, recall
Session 35: Unsupervised Learning
- What is clustering? (unsupervised learning algorithm)
- K-Means clustering with scikit-learn
- Choosing K using the Elbow Method
- Evaluating clusters (Inertia, Silhouette Score)
Session 36: Hands On Project
- Machine Learning Project
• Notebook presentation
• Review & feedback
Week 14
Session 37: Networking for Career Growth
• Networking as relationship-building
• Professional conversations in digital and physical spaces
• Initiating and maintaining connections
• Following up effectively
• Managing social anxiety professionally
• Creating value in networks
Power BI: Modeling & Advanced Visualization
Session 38: Power BI Overview & Data Loading
- Power BI Desktop interface
- Connecting to Excel, SQL, Python outputs
- Hands-on: Load datasets
Session 39: Power Query (Cleaning & Transformation)
- Remove errors & duplicates
- Split/merge, Pivot/Unpivot
- Hands-on: Transform data
Week 15
Session 40: Data Modeling
- Fact & dimension tables
- Star schema, relationships
- Hands-on: Build model
Session 41: DAX Basics
- Measures vs calculated columns
- SUM, COUNT, IF, DIVIDE
- Hands-on: Build KPIs
Session 42: Intermediate DAX & Time Intelligence
- CALCULATE(), FILTER()
- YTD, YOY
- Hands-on: Advanced KPIs
Week 16
Session 40: Visualization & Interactivity
- Charts, slicers, drill-through
- Conditional formatting
- Hands-on: Interactive report
Session 41: Advanced Visualization & Storytelling
- Bookmarks, tooltips
- Design best practices
- Hands-on: Story dashboard
Session 42: Power BI Service & Publishing
- Workspaces & dashboards
- Sharing & refresh
- Hands-on: Publish report
Week 17
Session 43: Security & Governance
- Row-Level Security (RLS)
- Dataset permissions
- Hands-on: Apply RLS
Session 44: CV Building & Professional Storytelling
- Skills-based vs experience-based CVs
- Translating learning into professional experience
- Writing impact-focused CV bullet points
- Structuring a clear, concise CV
- Portfolio and profile alignment
- Avoiding common CV mistakes
Introduction to Artificial Intelligence
Session 45: Intro to AI & GenAI for Analytics
- AI vs ML vs GenAI
- Using ChatGPT for Excel, SQL, Python
- Hands-on: AI-assisted analysis
Week 18
Session 46: AI for Productivity & Insights
- Prompting for EDA and reporting
- AI-assisted code generation
- Hands-on: Automate small tasks
Session 47: Intro to AI & GenAI for Analytics
- AI vs ML vs GenAI
- Using ChatGPT for Excel, SQL, Python
- Hands-on: AI-assisted analysis
Session 48: AI for Productivity & Insights
- Prompting for EDA and reporting
- AI-assisted code generation
- Hands-on: Automate small tasks
Week 19
Session 46: AI Ethics & Responsible Use
- Bias & fairness
- Data privacy
- Hands-on: Case discussion
Capstone Project
Session 47: Capstone Project Presentation & Evaluation
- End-to-end analytics project: Excel, SQL, Python, Power BI
- Final presentation & feedback
Session 48: Capstone Project Presentation & Evaluation
- End-to-end analytics project: Excel, SQL, Python, Power BI
- Final presentation & feedback
Week 20
Session 50: Workplace Readiness & Professional Conduct
- Understanding workplace dynamics
- Professional communication and boundaries
- Receiving and acting on feedback
- Managing conflict and expectations
- Accountability and reliability
- Navigating team environments
Session 51: Confidence, Visibility & Career Sustainability
- Presenting work with confidence
- Defending insights professionally
- Handling criticism and pushback
- Owning expertise without arrogance
- Long-term career mindset
- Transitioning from learner to professional