← Data Science & Analytics

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The complete curriculum

01 How to connect with mentors 1 lesson ▶

1. 1.1How to connect with mentors

02 Introduction 1 lesson ▶

1. 2.1Introduction to course

03 Excel Basics 5 lessons ▶

1. 3.1Basics
2. 3.2Worksheet Basics
3. 3.3Data Formats
4. 3.4Data Handling Basics Cut, Copy & Paste
5. 3.5Saving and Printing Basics

04 Essential Formulas 8 lessons ▶

1. 4.1Basic Formula Operations
2. 4.2Mathematical Functions 1
3. 4.3Mathematical Functions 2
4. 4.4Textual Functions Part 1
5. 4.5Textual Functions 2
6. 4.6Logical Functions
7. 4.7Date-Time Functions
8. 4.8Lookup functions (VLOOKUP,HLOOKUP,INDEX-MATCH)

05 Xlookup - Only for Excel 2021 and Office 365 4 lessons ▶

1. 5.1XLOOKUP as a replacement of VLOOKUP
2. 5.2Handling NA and approximate match in XLookup
3. 5.3Wildcard matching in XLOOKUP
4. 5.4Search modes

06 Data Tools 4 lessons ▶

1. 6.1Sorting, Filtering and Data Validation
2. 6.2Text-to-columns and remove duplicates
3. 6.3Advanced Filter option
4. 6.4Formatting Data and Tables

07 Excel Charts 13 lessons ▶

1. 7.1Importance of Data Visualization
2. 7.2Elements of Charts
3. 7.3The Easy way of Creating Charts
4. 7.4Bar and Column Charts
5. 7.5Formatting Charts Part 1
6. 7.6Formatting Charts Part 2
7. 7.7Line Charts
8. 7.8Area Charts
9. 7.9Pie and Doughnut Charts
10. 7.10Scatter plot or XY Chart
11. 7.11Waterfall Charts
12. 7.12Sparklines
13. 7.13Pivot Tables

08 Pivot Tables and Pivot Charts 2 lessons ▶

1. 8.1Pivot Tables
2. 8.2Pivot Charts

09 Map Charts- Only for Excel 2019 & above 1 lesson ▶

1. 9.1Maps Chart

10 Using ChatGPT with Excel 1 lesson ▶

1. 10.1Use ChatGPT For Excel Problems

11 Macros 1 lesson ▶

1. 11.1Macros

12 Importing Data from External Sources 1 lesson ▶

1. 12.1Importing Data from Websites Excel 2019 and 365

13 SQL Introduction 1 lesson ▶

1. 13.1Introduction

14 Installation and getting started 1 lesson ▶

1. 14.1Installing SQL Server and SSMS in your system

15 Database Basics 3 lessons ▶

1. 15.1What is SQL
2. 15.2Tables and DBMS
3. 15.3Types of SQL Commands

16 Fundamental SQL Statements 12 lessons ▶

1. 16.1CREATE
2. 16.2INSERT
3. 16.3Primary Key Foreign Key
4. 16.4Import data from file
5. 16.5Select
6. 16.6SELECT DISTINCT
7. 16.7WHERE
8. 16.8Logical Operators
9. 16.9UPDATE
10. 16.10DELETE
11. 16.11ALTER Part 1
12. 16.12ALTER Part 2

17 Restore and Backup 3 lessons ▶

1. 17.1Restore and Backup
2. 17.2Backup and Restore-Adventure Works DB
3. 17.3Creating tables using CSV files

18 Selection Commands: Filtering 3 lessons ▶

1. 18.1IN
2. 18.2BETWEEN
3. 18.3LIKE

19 Selection Commands:Ordering 3 lessons ▶

1. 19.1Side Lecture Commenting in SQL
2. 19.2ORDER BY
3. 19.3TOP (LIMIT)

20 Aliasing 1 lesson ▶

1. 20.1AS

21 Aggregate Commands 4 lessons ▶

1. 21.1COUNT
2. 21.2SUM
3. 21.3AVG
4. 21.4MIN MAX

22 GROUP BY 2 lessons ▶

1. 22.1GROUP BY
2. 22.2HAVING

23 Conditional Statement 1 lesson ▶

1. 23.1CASE WHEN

24 JOINS 11 lessons ▶

1. 24.1Introduction to Joins
2. 24.2Concepts of Joining and Combining Data
3. 24.3Preparing the Data
4. 24.4INNER JOIN
5. 24.5LEFT JOIN
6. 24.6RIGHT JOIN
7. 24.7FULL OUTER JOIN
8. 24.8CROSS JOIN
9. 24.9INTERSECT
10. 24.10EXCEPT
11. 24.11UNION ALL

25 Subqueries 3 lessons ▶

1. 25.1Part 1 - Subquery in WHERE Clause
2. 25.2Part 2 - Subquery in FROM clause
3. 25.3Part 3 - Subquery in SELECT Clause

26 Views and Indexes 2 lessons ▶

1. 26.1VIEW
2. 26.2INDEX

27 String Functions 7 lessons ▶

1. 27.1LENGTH
2. 27.2UPPER LOWER
3. 27.3REPLACE
4. 27.4TRIM LTRIM RTRIM
5. 27.5Concatenation
6. 27.6SUBSTRING
7. 27.7LIST AGGREGATION

28 Mathematical Functions 4 lessons ▶

1. 28.1CEIL FLOOR
2. 28.2RANDOM
3. 28.3ROUND
4. 28.4POWER

29 DATE TIME Functions 3 lessons ▶

1. 29.1Current date time
2. 29.2AGE - DATEDIFF
3. 29.3EXTRACT - DATE AND TIME PARTS

30 Pattern(String)Matching 3 lessons ▶

1. 30.1PATTERN MATCHING BASICS
2. 30.2PATTERN MATCHING PART 1
3. 30.3advance pattern matching part 2

31 Window functions 10 lessons ▶

1. 31.1Introduction to window functions
2. 31.2Introduction to Row numbers
3. 31.3Implementing row number in SQL
4. 31.4RANK and DENSERANK
5. 31.5NTILE
6. 31.6AVERAGE Window Function
7. 31.7COUNT WINDOW FUNC
8. 31.8SUM TOTAL
9. 31.9RUNNING TOTAL
10. 31.10LAG and LEAD

32 Data type conversion functions 1 lesson ▶

1. 32.1Converting number date to string and string to date

33 Deep dive into Python 52 lessons ▶

1. 33.1Python introduction and installation
2. 33.2Anaconda installation
3. 33.3Jupyter Walkthrough
4. 33.4Data Types and Basics of OOP
5. 33.5Numbers
6. 33.6Maths
7. 33.7Operator precedence
8. 33.8Strings Introduction
9. 33.9Type conversion and Escape Sequences
10. 33.10Strings 101
11. 33.11Booleans
12. 33.12Lists
13. 33.13List Methods
14. 33.14List Patterns and Unpacking
15. 33.15None
16. 33.16DIctionary
17. 33.17Dict Methods
18. 33.18Tuples
19. 33.19Sets
20. 33.20Set Methods
21. 33.21Conditional Logic
22. 33.22Truthy and Falsy
23. 33.23Ternary Operator
24. 33.24Short Circuiting ( Optional )
25. 33.25Logical Operators
26. 33.26Exercise - Logical Operators
27. 33.27== vs is
28. 33.28For Loop
29. 33.29Iterables
30. 33.30Exercise - Tricky Counter
31. 33.31range() and enumerate()
32. 33.32While Loop
33. 33.33Break , continue , pass
34. 33.34Exercise - Our first GUI
35. 33.35Exercise - Find Duplicates
36. 33.36Functions
37. 33.37Parameters & Arguments
38. 33.38Keyword arguments and Default parameters
39. 33.39Return
40. 33.40Funtions vs Methods
41. 33.41Docstring
42. 33.42Clean Code
43. 33.43args and kwargs
44. 33.44Exercise - Functions
45. 33.45Scope
46. 33.46Global and nonlocal
47. 33.47Pure Functions
48. 33.48Map()
49. 33.49Filter() & Zip()
50. 33.50Reduce()
51. 33.51Lambda
52. 33.52Exception Error handling

34 Projects 5 lessons ▶

1. 34.1Project Objective and Creating Tables in SQL
2. 34.2SQL Oueries across multiple tables for data extraction
3. 34.3Analysis, Validation and Visualization using Excel
4. 34.4Creating a Risk Prediction model in Python
5. 34.5Deploying Healthcare Risk stratification App

35 Modules, Packages and Libraries 5 lessons ▶

1. 35.1Modules
2. 35.2Packages
3. 35.3Ways to Import
4. 35.4Built -in Modules
5. 35.5Python Libraries

36 Numpy 12 lessons ▶

1. 36.1Numpy Introduction
2. 36.2Numpy Datatypes and Attributes
3. 36.3Creating Numpy Arrays
4. 36.4Numpy Random Seed
5. 36.5Viewing Arrays and Matrices
6. 36.6Manipulation of Arrays ( Arithmetic )
7. 36.7Manipulating Arrays ( Aggregate )
8. 36.8Variance and Standard Deviation
9. 36.9Reshaping and Transpose
10. 36.10Dot product
11. 36.11Comparison Operator and Sorting
12. 36.12Image to Numpy Array

37 Data Analysis using Pandas 8 lessons ▶

1. 37.1Pandas Overview
2. 37.2Series, Data Frames and CSV
3. 37.3Describing Data with Pandas
4. 37.4Selecting and Viewing Data
5. 37.5Asking the right questions
6. 37.6Manipulating Data using Pandas
7. 37.7Manipulating Data with Pandas 2
8. 37.8Apply Function

38 Data Visualization using Matplotlib, Seaborn and Plotly 20 lessons ▶

1. 38.1Matplotlib Introduction
2. 38.2Using Matplotlib
3. 38.3Matplotlib Workflow (Explicit Method)
4. 38.4Scatter and Bar plot
5. 38.5Histograms and Subplots
6. 38.6Subplots Alternate Method
7. 38.7Plotting from Pandas Series
8. 38.8Plotting from Pandas DataFrame
9. 38.9Plotting from Pandas DataFrame 2
10. 38.10Plotting from Pandas DataFrame 3
11. 38.11Plotting from Pandas DataFrame 4
12. 38.12Plotting from Pandas DataFrame 4
13. 38.13Plotting from Pandas DataFrame 6
14. 38.14Customizing our Plots
15. 38.15Customizing our Plots 2
16. 38.16Seaborn Introduction
17. 38.17Seaborn Univariate Analysis
18. 38.18Seaborn Bivariate Analysis
19. 38.19Seaborn Plotting Relationships
20. 38.20Plotly Express

39 Power BI 31 lessons ▶

1. 39.1Introduction to Power BI
2. 39.2Data Transformation + Data Types
3. 39.3Replace Text + Extract + Split
4. 39.4Trim + Clean
5. 39.5Assignment
6. 39.6Data Modelling
7. 39.7Visualization
8. 39.8ETL
9. 39.9Column Chart
10. 39.10Pie Chart
11. 39.11Line Chart
12. 39.12Table
13. 39.13Slicers
14. 39.14Filters
15. 39.15Tree Visualization
16. 39.16Logical DAX
17. 39.17Text DAX
18. 39.18DateTime DAX
19. 39.19Problem-1
20. 39.20Problem-2
21. 39.21Problem-3
22. 39.22Problem-4
23. 39.23Problem-4 Extended
24. 39.24Problem-5
25. 39.25Problem-6
26. 39.26Bookmarks
27. 39.27RLS
28. 39.28Field Parameters
29. 39.29AI Visuals + Quick Measures
30. 39.30Folder Problem
31. 39.31SQL+PowerBI

40 Job Readiness & Placement Support 6 lessons ▶

1. 40.1How to build a Resume
2. 40.2Customizing the Resume as per specific Job
3. 40.3Interview Preparation Guidelines
4. 40.4Short Mock Interview Flow
5. 40.5How to Apply for Jobs
6. 40.6Profile Enhancement and Upskilling

Tools you'll use

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