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Course Content
Module 00: Introduction to BI Analytics Bootcamp
0/5
1. What is Business Analytics ?
11:16
2. BI Analytics Jobs in Local Market
08:24
3. BI Analytics Jobs in Abroad (Remote Job)
07:26
4. What to Learn in BI Analytics
11:18
5. What you will Learn in this bootcamp
18:59
Module 0.5: Your Course Conduct Links and groups
0/2
Whatsapp Paid Group
Google Classroom Paid Link
Module 1.1 – Week 0.5 – Excel Mastery Fundamentals
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Class 01 – Excel Interface and Workflow
30:52
Class 02 – Data Entry & Basic Formulas
34:06
Class 03 – Data Cleaning & Preparation
40:25
Class 04 – Data Validation & Logical Functions
43:36
Class 05 – VLOOKUP, INDEX & MATCH
34:35
Class 06 – Statistical Formulas
20:44
Class 07 – Date Formulas & Pivot Tables
31:17
Excel Quiz 01
Module 1.2 – Week 01 – Excel Mastery Live
0/3
Excel Mastery – Live Class 01
Excel Mastery – Live Class 02 (Project 01)
Excel Assignment 01
Module 1.3 – Week 02 – Excel Mastery Live
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Excel Mastery – Live Class 03
Excel Mastery – Live Class 04 (Project 02)
Excel Assignment 02
Excel Quiz 02
Module 2.1 – Week 2.5 – Google Analytics Fundamentals
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Class 01 – Google Analytics & Excel Integration
24:43
Class 02 – Excel Advanced Lookup Techniques
20:45
Class 03 – Google Sheets Lookup & Array Functions
19:00
Class 04 – Google Sheets Query, Array, and IF Functions
21:43
Google Analytics Quiz 01
Module 2.2 – Week 03 – Google Analytics Live
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Google Analytics – Live Class 01
Google Analytics – Live Class 02 (Project 01)
Google Analytics Assignment 01
Module 2.3 – Week 04 – Google Analytics Live
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Google Analytics – Live Class 03
Google Analytics – Live Class 04 (Project 02)
Google Analytics Quiz 02
Module 3.1 – Week 4.5 – Power BI with DAX Fundamentals
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Class 01 – Power BI Foundation: Setup & Initial Workflow
41:35
Class 02 – Data Transformation & Power Query Fundamentals
43:21
Class 03 – Advanced Power Query: Data Enrichment & Optimization
46:42
Class 04 – DAX Fundamentals: Aggregations & Error Handling
41:01
Class 05 – Data Visualization Principles & Basic Charting
44:00
Class 06 – Interactive Dashboard Design & Slicer Logic
40:09
Class 07 – Advanced Visualization & Dashboard Storytelling
43:51
Class 08 – Advanced Geospatial Analysis & ArcGIS Integration
24:55
Class 09 – Data Analytics Project: End-to-End Dashboard Development
31:55
Class 10 – Final Project Recap: Building the Summary Dashboard
29:10
Power BI Quiz 01
Module 3.2 – Week 05 – Power BI with DAX Live
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Power BI – Live Class 01
Power BI – Live Class 02 (Project 01)
Power BI Assignment 01
Module 3.3 – Week 06 – Power BI with DAX Live
0/4
Power BI – Live Class 03
Power BI – Live Class 04 (Project 02)
Power BI Assignment 02
Power BI Quiz 02
Module 4.1 – Week 6.5 – SQL Fundamentals
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Class 01 – SQL for Big Data: Analysis, Quality, and Window Functions
25:16
Class 02 – SQL Fundamentals: Precise Data Retrieval and Formatting
20:19
Class 03 – SQL Aggregations: Summarizing and Processing Sales Data
19:31
Class 04 – SQL Conditional Logic and Post-Aggregation Filtering
18:21
Class 05 – Temporal Analysis: Date Functions and Time-Series Trends
17:31
Class 06 – Data Quality Assurance and Value Classification
18:10
Class 07 – Advanced SQL Architecture: Subqueries, Nesting, and CTEs
23:28
Class 08 – Window Functions: Advanced Analytics and Data Ranking
18:00
Class 09 – Relational Joins, String Manipulation, and Null Logic
21:45
SQL Quiz 01
Module 4.2 – Week 07 – SQL Live
0/3
SQL – Live Class 01
SQL – Live Class 02 (Project 01)
SQL Assignment 01
Module 4.3 – Week 08 – SQL Live
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SQL – Live Class 03
SQL – Live Class 04 (Project 02)
SQL Assignment 02
SQL Quiz 02
Module 5.1 – Week 09 – Big Data Analytics Live
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Big Data – Live Class 01
Big Data – Live Class 02 (Project 01)
Big Data Assignment 01
Big Data Quiz 01
Module 5.2 – Week 10 – Big Data Analytics Live
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Big Data – Live Class 03
Big Data – Live Class 04 (Project 02)
Big Data Quiz 02
Module 6.1 – Week 10.5 – Python for Data Analytics Fundamentals
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Class 01 – Python Fundamentals for Beginners
45:35
Class 02 – Python Data Structures: Lists & Tuples
45:00
Class 03 – Conditional Logic, List & Dictionaries
43:00
Class 04 – Loops & Functions
38:10
Class 05 – Python Modules, Math, and File Handling
44:30
Class 06 – NumPy Arrays & Matrix Operations
40:30
Class 07 – File Handling & Pandas Basics
46:00
Class 08 – Python Strings, Lists & Dictionaries
46:40
Class 09 – Python Conditional Logic & Loops
40:20
Python Quiz 01
Module 6.2 – Week 11 – Python for Data Analytics Live
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Python – Live Class 01
Python – Live Class 02 (Project 01)
Python Assignment 01
Module 6.3 – Week 12 – Python for Data Analytics Live
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Python – Live Class 03
Python – Live Class 04 (Project 02)
Python Assignment 02
Python Quiz 02
Module 7.1 – Week 12.5 – Statistical Analytics Fundamentals
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Class 01 – Linear Algebra for Data Science: Vectors & Matrices
32:50
Class 02 – Matrix Algebra: Transformations and Structural Operations
31:29
Class 03 – Statistical Foundations: From Description to Inference
30:45
Class 04 – Data Classification and Visual Representation
33:48
Class 05 – Descriptive Statistics: Measures of Central Tendency
43:10
Class 06 – Descriptive Statistics: Measures of Variability and Distribution
35:25
Class 07 – Statistical Shape Analysis and Python Implementation
33:30
Class 08 – Sampling Methodologies: Theory and Python Implementation
41:10
Class 09 – Systematic and Cluster Sampling: Advanced Selection Logic
52:05
Class 10 – Probability Theory: Foundations of Uncertainty
28:25
Class 11 – Random Variables and Probability Distributions in Data Science
30:40
Class 12 – Discrete Probability Distributions
31:05
Class 13 – Continuous Probability Distributions: Modeling Smooth Intervals
38:10
Statistics Quiz 01
Module 7.2 – Week 13 – Statistical Analytics Fundamentals Live
0/3
Statistics – Live Class 01
Statistics – Live Class 02 (Project 01)
Statistics Assignment 01
Module 7.3 – Week 14 – Statistical Analytics Fundamentals Live
0/4
Statistics – Live Class 03
Statistics – Live Class 04 (Project 02)
Statistics Assignment 02
Statistics Quiz 02
Module 8.0 – Week 15 – BI Analytics Career Guideline
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Class 01 – GitHub, Kaggle & Web-Based Resume Writing
Class 02 – Local & Remote Job Finding Strategy with Portfolio Building
Module 9.0 – Week 16 – Tableau (Bonus Module)
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Class 01 – Tableau Fundamentals & Basic Charts
01:01:50
Class 02 – Advanced Visualization in Tableau
59:30
Class 03 – Data Analysis & Visual Exploration in Tableau
59:10
Class 04 – Call Center Data Analysis in Tableau
57:35
Class 05 – Connecting to Data Servers and Analyzing Insights in Tableau
51:40
Class 06 – Sales Analysis & KPI Dashboard in Tableau
55:55
Module 10.0 – Week 17 – Machine Learning (Bonus Module)
17 Hours 20 Minutes Lecture series
0/11
Class 01
01:26:34
Class 02
01:50:27
Class 03
01:49:28
Class 04
02:12:03
Class 05
01:45:37
Class 06
01:25:37
Class 07
02:00:17
Class 08
01:14:22
Class 09
01:28:26
Class 10
43:21
Practice Materials
Old Module 9: All Python Quizzes
All 4 Python quizzes are here
0/4
Python Quiz 01
Python Quiz 02
Python Quiz 03
Python Quiz 04
Old Module 10: All Excel Quizzes
All 4 Excel Quizzes are here
0/4
Excel Quiz 01
Excel Quiz 02
Excel Quiz 03
Excel Quiz 04
Business Intelligence Analytics Job Ready Live Bootcamp

Project 2 – GitHub Activity Trend Analysis Using BigQuery Public Datasets

📌 Topics Covered

  • Analyzing GitHub public event datasets
  • Using CTEs for multi-step aggregations
  • Tracking repository contributions and programming language trends
  • Windowed analysis of commit activity

📝 Project Summary

This project focuses on querying GitHub’s massive public dataset to uncover open-source trends. Learners analyze repositories, contribution patterns, and programming language growth using SQL. The structured queries provide insights for developer relations or technology research.

✅ What You Will Learn

  • Identify top programming languages and repositories
  • Track commit activity by day and hour
  • Compare Python vs JavaScript repository growth over time
  • Use CTEs for stepwise aggregation
  • Analyse contribution trends and visualize results using Looker Studio or Google Sheets

 

Note to Students –

Live Classes will held on Google Meet.
Mentor will provide files, dataset in the Google Classroom.
Class video will be provided on Google Classroom.

Click “Mark as Complete” button.

Good Luck.

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