Business Intelligence/Data Analyst Bootcamp
Course Instructor
OdinSchool
FREE
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Course Overview
Schedule of Classes
Course Curriculum
1 Subject
Business Intelligence/Data Analyst
18 Exercises • 451 Learning Materials
Step Up
1. Introduction to Computers and Operating Systems
2. Internet and Web Browsing
3. Email and Online Communication
4. Word Processing and Document Management
5. Spreadsheets and Data Management
6. Text Editors vs. Integrated Development Environments (IDEs)
7. Graphical User Interface (GUI)
8. Command-Line Interface (CLI)
9. Introduction to Programming and Data Science
SQL
MySQL Workbench Installation for Windows
MYSQL Workbench Installation For MAC
Importing SQL files in Workbench
1. Introduction to SQL
2. Create Database
3. Insert
4. Alter
5. Select
6. String Functions
7. Numeric and Temporal functions
SQL functions- Order by, Limit
Like and ILike (wildcards)
Aggregate functions in SQL
Group By
Having
SQL Joins
Inner Join
Full outer join
Left Outer Join
Python
1. Google Colab - Part 1
2. Google Colab - Part 2
How to read a file in Jupyter Notebook
How to read a file in Google Colab
Anaconda Installation
3. Understanding Programming
4. Python properties and applications
5. Variables and Values
6. Data Types-Integer
7. Data Types-Float
8. Data Types-Boolean
9. Data Types- String
10. Single and Multi-line commenting
11. Input, output and formatting
12. Indexing & Slicing in Strings
13. Conditionals
14. If statements
15. Else & Elif Statement
16. Logical operations in conditionals
Statistics
1. What statistics is and what data are?
2. Qualitative data (nominal and ordinal)
3. Quantitative data (discrete and continuous)
4. Sample and Population
5. Sampling techniques
6. Measures of Central Tendency (Mean, median and mode)
7. Measures of Dispersion (variance, sd and IQR) and skewness
8. Bar plot
9. Pie chart
10. Histograms
11. Scatter plots
12. Box whiskers-Plot
13. Graph hands on python
14. Intro to probability
15. Important concepts (event, set, subset, sample space)
16. Important concepts (intersection, union, complement)
17. Disjoint, non-disjoint and independent event
18. Conditional probability
19. Normal distribution
20. Bayesian inference
21. Binomial distribution
22. Poisson distribution
23. Central Limit Theorem
24. Confidence Interval
25. Null and alternative hypothesis
26. One tailed and two tailed tests
27. Significance level and p value
28. Type I and Type II Errors
29. Statistical power
30. T distribution and degree of freedom
31. One sample T test
32. Independent sample T test
33. Paired T test
34. F distribution
35. One way Anova
36. Two way Anova
37. Contingency Table
38. Pearson's correlation coefficient
39. Chi-square Test
Statistics - Live Session - Recording - Week 1 - Day 2
Statistics - Live Session - Recording - Week 2 - Day 1
Statistics - Live Session - Recording - Week 2 - Day 2
Statistics - Live Session - Recording - Week 3 - Day 1
Statistics - Live Session - Recording - Week 3 - Day 2
EDA
1.Basic Exploration
2.Missing Values
3.Outlier
4.Dealing with skewed data
5.Data Visualization 1
6.Data Visualization 2
7.Binning
8.Dummy variable
9.Feature scaling
Machine Learning
1.Scalar ,vector, matrix and arrays
2.Matrix multiplication
3.Null and alternative hypothesis
4.One tailed and two tailed tests
5.Significance level and p value
6.Type I and Type II Errors
7.What is a Decision Tree
8.Decision Tree in Brief
9.Terminologies used
10.Case study - EDA
11.Case study - ML
12.What is Random Forest?
13.Working Philosophy
14.Terminologies & Real-life examples
15.Case Study - ML
16.What is K-nearest-neighbour?
17.How does this work?
18.Walk through Sci-kit website
19.Case study - ML
20.Basic of Support Vector Machine
21.Why the name
22.Kernel, Gamma and C value
23.Case Study - ML
24.What is Naive Bayes Theorem
25.Why the name
26.Case study - ML
27.What is unsupervised learning?
28.What is k-means & clustering
29.Case Study - ML
30.What is Market Basket Analysis
31.How does it work
32.Case study - ML
33.Analogy of TSA
34.Parts of TSA
35.Intro to TSA
36.Rolling Stats
37.ACF and PACF
38.Understanding PCA
39.Case study - ML
40.Understand NLP in detail
41.Case Study - ML
42. Deep Learning - ANN
43.1 Deep Learning - CNN (Part 1 )
43.2 Deep Learning - CNN (Part 2)
44.1 RNN - Part 1
44.2 RNN - Part 2
44.3 RNN - Part 3
45.1 NLP PART 1
45.2 NLP- PART 2
45.3 NLP - Part 3
45.4 NLP- PART 4
45.5 NLP- PART 5
45.6 NLP - part 6
45.7 NLP- PART 7
45.8 NLP- PART 8
46.1 Open CV - Part 1
46.2 Open CV - Part 2
46.3 Open CV - Part 3
46.4 Open CV - Part 4
46.5 Open CV - Part 5(a)
46.6 Open CV - Part 5 (b)
46.7 Open CV - Part 6
46.8 Open CV - Part 7(a)
46.9 Open CV - Part 7(b)
47.1 Scikit-Image - Part 1
47.2 Scikit-Image - Part 2
47.3 Scikit-Image - Part 3
47. 4 Scikit-Image - Part 4
48. Reinforcement learning
EDA+ML - Live Session - Recording - Week 1 - Day 1
External Link
EDA+ML - Live Session - Recording - Week 1 - Day 2
EDA+ML - Live Session - Recording - Week 2 - Day 1
EDA+ML - Live Session - Recording - Week 2 - Day 2
External Link
EDA+ML - Live Session - Recording - Week 3 - Day 1
External Link
EDA+ML - Live Session - Recording - Week 3 - Day 2
PySpark
1.BIG DATA HISTORY PART 1
2.BIG DATA HISTORY PART 2
3.RDD Introduction
4.spark ecosystem
5.spark_lazy_evulation
6.spark_RDD_Setup_On_Google_Colab
7.Spark context & Spark Session
8.Spark RDD Transformation - Part 1
9.Spark RDD Transformation - Part 2
10.Spark RDD Transformation - Part 3
11.RDD ACTION
12.DataFrame - Part 1
13.DataFrame - Part 2
14.Spark-shell, spark-submit & running spark in local
PySpark - Live Session - Recording - Week 1 - Day 1
PySpark - Live Session - Recording - Week 1 - Day 2
External Link
PySpark - Live Session - Recording - Week 2 - Day 1
PySpark - Live Session - Recording - Week 2 - Day 2
External Link
PySpark - Live Session - Recording - Week 3 - Day 1
External Link
PySpark - Live Session - Recording - Week 3 - Day 2
Power BI
Power BI Course Material
ZIP
Module 1
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1. Clustered or Stacked Chart
2. Treemaps
3. Area Chart
4. Donut Chart
5. Cards Multicard
Module 2
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1. Gauge Chart
2. Combo Charts
3. Funnel Charts
Module 3
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1. Scatter Plot
2. Maps
3. Dynamic Title
4. KPIs
5. Key influencers chart
6. Waterfall charts
Module 4
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1. Decomposition Tree
2. Q and A Visual
3. Smart Narrative
Module 5
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1. Import Custom Visuals
2. Add Visuals Using Python
Module 6
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1. Static Row - Level Security
2. Dynamic Row - Level Security
Module 7
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1. Drill Down
2. Drill Through
3. Visual Tooltips and ToolTip Page
Module 8
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1. Data Fields
2. Configuring Conditional Formatting
3. Configuring Small Multiples
4. Configuring the Report Page
5. Color Combinations
6. Data Analytics Pane
7. Creating hierarchies
Module 9
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1. Difference between Service and Desktop
2. Using Microsoft account
3. Using office_email
Module 10
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1. Define and Measure
2. Evaluate
3. Variable
Module 11
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1. Visualization End to End Project
Module 12
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1. SWITCH, KEEPFILTERS, ALLSELECTED
2. RANKX , SELECTEDVALUE , TOPN
ALL
Module 13. Azure Fundamental
External Link
Module 14. Importing Data from various Sources
External Link
Module 15. Import Direct Query and Live Connection
External Link
Module 16. What if Parameter
External Link
Module 17. Advance Power Query
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1. Advance Power Query
2. Invoke Custom Functions
Module 18. Advance DAX - Currency Conversion
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1. M Language
2. Currency Conversion
Module 19. DAX
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1. DAX RT
2. Coalesce DAX
3. Path DAX
Module 20. DAX Engine
Module 21. Introduction to Paginated Report
Module 22. PL 300 Certification Preparation
Module 23. Dataset Data Flow
Module 24. Best Practices for Power BI Reporting
Module 25. Power BI services (Pro and Premium Per User)
Module 26. Advance Power BI service (Apps, PPU, Deployment Pipelines)
Module 27. Service Incremental Refresh, Workspace Role
Module 28. Dynamic RLS, Configuring Subscription, Configuring
Module 29. Paginated Report builder. Creating Charts, Table, Row and Column Groups
Module 30. Creating Complete Report with formatting, theme, etc as per customer requirements
Module 31. Integrate Power BI reports dashboard with MS team and Power Point
Module 32. End to End Project
Power BI - Live Session - Recording - Week 1 - Day 1
Power BI - Live Session - Recording - Week 1 - Day 2
Power BI - Live Session - Recording - Week 2 - Day 1
Power BI - Live Session - Recording - Week 2 - Day 2
Power BI - Live Session - Recording - Week 3 - Day 1
External Link
Power BI - Live Session - Recording - Week 3 - Day 2
Azure
1.Introduction to Azure
2.Cloud basics
3.Azure services - Virtual Machines
4.Azure services - Azure SQL - Database
5.Azure Storage
6.Azure Sql Databases
7.Azure sql databases 1
8.Stream Analytics
9. SSMS Installation Video
10."Create Azure Data Factory Account Azure Data Factory Studio Overview "
11."Create Azure SQL Database Create First ADF Pipeline"
12."Create Dynamic Linked Service and Dataset "
13. Linked Service Parameterization in Data factory
14.Lookup Activity in Azure Data Factory
15.System Variables in ADF
16.Web activity in ADF
17. Set Variable in Azure Data Factory
18.Data Flow in ADF
19."Debug Pipeline in ADF Schedule Trigger in ADF "
20.Tumbling Window and Storage Event in ADF
21."Global Parameter in ADF "
22.Monitoring & Alert Rule in ADF
23.Introduction : Azure DataBricks
24.What is Databricks workspace?
25.Azure Databricks Workspace
26.Azure Databricks Utilties(dbutils)
27."Azure Databricks"
28.Create SQL Warehouse in Azure Databricks
29. Azure Databricks
30.Azure Databricks Mount ADLS gen 2
31.Azure Databricks Integration Delta lake Architecture
32.Azure Databricks Streaming
33.Azure Stream Analytics
34. Introduction to Azure Synapse Analytics and Creating Workspace
35.Analyse Data with Serverless and Dedicated SQL pool
36.Analyze data with Server less Spark Pool in Azure Synapse Analytics
37.Analyse data in Storage account and Integrate pipeline in Azure Synapse Analytics workspace
38.Monitor and add an Administrator to the synapse
39.Overview of Azure purview
40.Azure Synapse SQL Architecture
41.Serverless SQL pool in Azure Synapse analytics
42.Create External Data source in azure synapse analytics
43.Create External file format in Synapse
44.CETAS with synapse SQL in Synapse Analytics
45.CTAS with synapse sql in synapse analytics
DE
DE - Live Session - Recording - Week 1 - Day 1
DE - Live Session - Recording - Week 1 - Day 2
DE - Live Session - Recording - Week 2 - Day 1
External Link
DE - Live Session - Recording - Week 2 - Day 2
External Link
Tableau
1 Get Started
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1.1 Introduction and Installation
1.2 Basic Tableau Functions
2 Working with Charts
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2.1 Working with Time series
2.2 Creating a map, working with hierarchies & calculated fields
2.3 Understanding Aggregations and granularity
2.4 Creating scatter plot, applying filters
3 Using Multiple Datasets
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3.1 Joining and Blending
3.2 Creating a dual axis chart and a tree map
4 Dashboards and Stories
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4.1 Creating dashboard, advanced dashboard interactivity
4.2 Creating stories
5 Advanced Tableau Functions
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5.1 Tableau Parameters
5.2 Tableau Forecasting
5.3 Relationships in Tableau
ETL
ETL Installation
External Link
ETL - Live Session - Recording - Week 1 - Day 1
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ETL - Live Session - Recording - Week 1 - Day 2
External Link
ETL - Live Session - Recording - Week 2 - Day 1
External Link
ETL - Live Session - Recording - Week 2 - Day 2
External Link
Business Intelligence
Business Intelligence - Live Session - Recording - Week 1 - Day 1
Business Intelligence - Live Session - Recording - Week 1 - Day 2
External Link
Advanced Excel
Advance Excel - Live Session - Recording - 1
Advance Excel - Live Session - Recording - 2
Advance Excel - Live Session - Recording - 3
Python Challenges
Challenge - 1
External Link
Challenge - 2
External Link
CAP - E Learning Videos
Module 1
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1. The word that has haunted us most of our lives
2. The Brain & Learning
Video link
External Link
3.1. The Brain & Learning New skills - 1
Video link
External Link
3.2 The Brain & Learning New Skills - 2
4. Formula for learning any Skill & Why certain people learn skills faster?
Video link
External Link
5. How to learn effectively
6. The key factor for learning
Module 2
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1. Introduction & Embracing fear
Video Link
2. Response to fear - FFF
Video Link
External Link
Video Link
External Link
3. How to be more confident - Tip No 1
4. How to be more confident - Tip No 2
5. How to be more confident - Tip No 3
6. Quick & simple confidence builder tips
7. Conclusion
Module 3
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1. Introduction & activity
2. What are emotions
3. Are emotions good or bad
Video Link
External Link
4. What is Emotional Intelligence ?
5. Steps to improve Emotional Intelligence
6. Cycle of Emotional Intelligence
7. Conclusion
Module 4
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1. Introduction and Activity
2.1. Habit no 1 - Beat Procrastination -1
Video Link
External Link
2.2. Habit no 1 - Beat Procrastination - 2
Video Link
External Link
3. Habit no 2 - Mono vs Multi tasking
4. Habit no 3 - Schedule everything
5. Habit no 4 - 1-4-1 technique
6. Habit no 5 - Habit Stacking
Video Link
External Link
7. Habit no 6 - Prioritization
Video Link
External Link
8. Habit no 7&8 - Have a hobby - Sleep or Exercise
9. Conclusion
Bonus video
External Link
Module 5
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1.Introduction to Problem Solving
2. Work/Problem solving
3. Evolution of Design thinking
4.1. Step 1 - Empathy -1
Video Link
External Link
4.2. Step 1 - Empathy - 2
5. Step 2- Define the Problem
6. Step 3 - Ideation
7. Step 4 and 5 - Prototyping and Testing
The word that has haunted us most of our lives - Questionnaire
Exercise
The Brain & Learning - Questionnaire
Exercise
Formula for learning any Skill & Why certain people learn skills faster? - Questionnaire
Exercise
How to learn effectively - Questionnaire
Exercise
The key factor for learning - Questionnaire
Exercise
Introduction & Embracing fear - Questionnaire
Exercise
Response to fear - FFF - Questionnaire
Exercise
How to be more confident - Tip No 1 - Questionnaire
Exercise
How to be more confident - Tip No 2 - Questionnaire
Exercise
How to be more confident - Tip No 3 - Questionnaire
Exercise
Quick & simple confidence builder tips - Questionnaire
Exercise
Conclusion - Questionnaire
Exercise
What are emotions? - Questionnaire
Exercise
Are emotions good or bad? - Questionnaire
Exercise
What is Emotional intelligence? - Questionnaire
Exercise
Steps to improve Emotional Intelligence - Questionnaire
Exercise
Cycle of Emotional Intelligence - Questionnaire
Exercise
Habit no 1 - Beat procrastination - Questionnaire
Exercise
Data Analytics using Microsoft Excel
Course Overview
External Link
Communicating the Story that Data Insights Represent
Introduction
External Link
Role of Data Insights in Decision Making
External Link
Communicating Visually and Effectively Part 1
External Link
Communicating Visually and Effectively Part 2
External Link
Summary
External Link
Visual Interpretation and Communication of Data
Data Interpretation - Overview
External Link
Data Interpretation - Meaning, Benefits and Challenges
External Link
Data Interpretation - Example
External Link
Analyzing Quantitative Data
External Link
Analyzing Qualitative Data
External Link
Chart Thought Starter: Do's and Don’ts
Psychology of Data Visualization: Overview
External Link
Psychology of Data Visualization: Bringing our Visualization from Good to Great
External Link
Cognitive Research on Human Preference and Behaviour
External Link
Smart Data Discovery - Cognitive Psychology: The Science of Perception
External Link
Smart Data Discovery - Role of Data Discovery in Self-Service BI
External Link
Using Microsoft Excel as Story-Telling Tool
Introduction to the module
External Link
Explore Preliminary Patterns
External Link
Organizing data in a Hierarchy
External Link
Working with Excel Charts and Sparklines & Analyzing data trends with Sparklines - Part 1
External Link
Working with Excel Charts and Sparklines & Analyzing data trends with Sparklines - Part 2
External Link
Working with Excel Charts and Sparklines & Analyzing data trends with Sparklines - Part 3
External Link
Data Insights—360° View
Analyzing impact of data metrics by dimensions
External Link
Linear regression (Through scatter plots)
External Link
Pareto Analysis
External Link
Using decomposition tree concepts in excel for root cause analysis
External Link
Using Microsoft Excel Self-Service BI as a Storytelling Tool
Introduction
External Link
Practice Data Modelling through Power Pivot - Demo Time
External Link
Practice Data Modelling through Power Pivot - Part 2
External Link
Practice Data Modelling through Power Pivot - Part 3
External Link
The Last Mile - The Last Mile: Using Maps to Showcase Data—Advanced Visualization
External Link
The Last Mile - The Last Mile: Using Maps to Showcase Data—Advanced Visualization (Cont’d)
External Link
Download - Analytics_Practice Datasets
Analytics Practice Datasets
ZIP
Course Instructor
OdinSchool
180 Courses • 19831 Students
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