Hands-On Data Analytics Courses in Bangalore to Boost Your Career
Tools & Technologies
- Excel (Advanced)
- SQL (MySQL / PostgreSQL)
- Power BI, Tableau
- Python (Pandas, Matplotlib, Seaborn)
- Cloud: AWS, GCP, Azure
- Jupyter Notebook, Git, Google Sheets, OpenRefine
Program Highlights
- 11 Expert-Led Modules
- 5+ Industry Projects + 1 Capstone
- Wingslide Technologies Certification
- Resume, LinkedIn, and Interview Prep
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Data Analytics Course Curriculum
- What is Data Analytics?
- Types: Descriptive, Diagnostic, Predictive, Prescriptive
- Analytics Lifecycle & Use Cases Across Domains
- Overview of Tools: Excel, SQL, Python, BI Platforms
- Roles in the Analytics Ecosystem
- Data Cleaning, Formatting, and Transformation
- Lookup & Reference Functions: VLOOKUP, XLOOKUP, INDEX-MATCH
- Pivot Tables, Pivot Charts, Dynamic Dashboards
- Scenario Analysis, Goal Seek, Solver
- Power Query for Advanced Data Preparation
- Excel + Power BI Integration
- RDBMS Concepts, ER Diagrams
- SQL Queries: SELECT, WHERE, GROUP BY, JOINs
- Nested Queries, Subqueries, Views
- Window Functions: RANK, ROW_NUMBER, LAG, LEAD
- Data Transformation & Aggregation Techniques
- Hands-on with MySQL/PostgreSQL
- Real-world SQL Projects (Sales, HR, Finance datasets)
- Power BI Desktop Interface
- Data Modeling & Relationships
- DAX for Calculated Columns and Measures
- Creating Interactive Dashboards
- Slicers, Filters, Drill-downs, Bookmarks
- Publishing Reports to Power BI Service
- Role-Level Security (RLS) and Scheduled Refresh
- Project: Sales & Marketing KPI Dashboard
- Tableau Desktop Interface Overview
- Data Connection, Blending, and Joins
- Building Charts: Bar, Line, Heatmaps, Geo Maps
- Filters, Parameters, and Calculated Fields
- Creating Dashboards with Interactions
- Storytelling with Tableau Stories
- Project: E-commerce Revenue Dashboard
- Python Basics: Lists, Dictionaries, Loops, Functions
- NumPy & Pandas for Data Manipulation
- Matplotlib & Seaborn for Visualizations
- EDA Techniques in Python
- Combining Python with SQL for End-to-End Analytics
- Descriptive Statistics: Mean, Median, Mode, Std Dev
- Probability Basics, Distributions
- Inferential Statistics: Hypothesis Testing
- Correlation, Regression
- Real-world Interpretation in Business Scenarios
- Data Profiling, Missing Values, Outliers
- Feature Engineering Basics
- Pattern Detection and Business Hypotheses
- Telling Stories from Data using Visual Aids
- EDA with Excel, SQL, Python, and BI Tools
- ETL vs ELT
- Manual ETL with SQL & Excel
- Introduction to ETL Tools: OpenRefine, Talend (optional)
- Automation Ideas using Power Query, Python
- End-to-End Mini Project: Data Collection → Cleaning → Visualization
- Introduction to AWS, GCP, Azure
- AWS: S3, Athena, Redshift, QuickSight, Glue
- GCP: BigQuery, Cloud Storage, Looker Studio
- Azure: Synapse Analytics, Data Lake, Power BI
- Data Warehousing Concepts (OLAP vs OLTP)
- Building Cloud-Connected Dashboards
- Project 1:
- Retail Sales Performance Dashboard (Power BI + SQL)
- Project 2:
- HR Attrition and Retention Analysis (Excel + Tableau)
- Project 3:
- E-commerce Funnel Optimization (Python + Power BI)
- Project 4:
- Marketing ROI & Spend Analysis (Excel + SQL)
- Capstone Project: End-to-End Case Study with Presentation & Review
- GitHub Portfolio, LinkedIn Projects, Resume Optimization
