Course curriculum

Click on Show More to check the entire contents 👇👇

    1. Welcome Page - Free Preview

      FREE PREVIEW

    2. Welcome to the Course!!

    3. Join our Community!!

    4. What is Data Analytics

    5. Importance of Data Analytics

    6. Types of Data

      FREE PREVIEW

    7. Types of Statistical Analysis

    8. Steps to obtain a Data Analytics solution

    9. 1 Business Understanding

    10. 2 Data Understanding

    11. 3 Data Collection

    12. 4 Data Preparation

    13. 5 Data Modelling

    14. 6 Deployment

    15. Use Case

    1. Course Contents

    2. Python Introduction

      FREE PREVIEW

    3. Variables & Keywords

    4. Datatypes & Operators

    5. Data Structures - Lists

    6. Data Structures - Tuples

    7. Data Structures - Sets

    8. Data Structures - Dictionary

    9. Loops & Iteration

    10. Functions in Python

    11. File Handling

    12. Map Reduce Filter

    13. OOPS Concepts

    14. Control Structures in Python

    15. Python Quiz #1

    16. NumPy

    17. Pandas

    18. Data Visualization

    19. Matplotlib

    20. Seaborn

    21. Python Quiz #2

    1. Course Contents

    2. Agenda

    3. Data Analytics/Science Process

      FREE PREVIEW

    4. What is EDA

    5. Visualization

    6. Steps involved in EDA (Data Sourcing)

    7. Steps involved in EDA (Data Cleaning)

    8. Handle Missing Values (Theory)

    9. Handle Missing Values (Code)

    10. Feature Scaling

    11. Feature Scaling (Standardization)

    12. Feature Scaling (Normalization)

    13. Feature Scaling (Code)

    14. Outlier Treatment (Theory)

    15. Outlier Treatment (Code)

    16. Invalid Data

    17. Types of Data

    18. Types of Analysis

    19. Univariate Analysis

    20. Bivariate Analysis

    21. Multivariate Analysis

    22. Numerical Analysis

    23. Analysis (Code)

    24. Derived Metrics

    25. Feature Binning (Theory)

    26. Feature Binning (Theory)

    27. Feature Binning (Code)

    28. Feature Encoding

    29. Feature Encoding Detailed

    30. Feature Encoding (Code)

    31. Case Study

    32. Data Exploration (Case Study)

    33. Data Cleaning (Case Study)

    34. Univariate Analysis (Case Study)

    35. Bivariate Analysis (Case Study)

    36. Bivariate Analysis (Case Study)

    37. EDA Report (Case Study)

    38. EDA Quiz

    1. Course Contents

    2. Intro to Stats

    3. Chapter 1 - Agenda

    4. Descriptive Stats

    5. Inferential Stats

    6. Qualitative Data

    7. Quantitative Data

    8. Chapter 2 - Agenda

    9. Population vs Sample

    10. Why sampling is important?

    11. Types of sampling

    12. Probability Sampling

    13. Cluster Random Sampling

    14. Non probability sampling

    15. Chapter 3 - Agenda

    16. Measures of Central Tendency

    17. Mean

    18. Median

    19. Mode

    20. Measures of Dispersion

    21. Range

    22. IQR

    23. Mean Deviation

    24. Variance & Standard Deviation

    25. Why n-1 and not n

    26. Chapter 4 - Agenda

    27. Probability

    28. Addition Rule

    29. Independent Events

    30. Cumulative Probability

    31. Conditional Probability

    32. Bayes Theorem Part 1

    33. Bayes Theorem Part 2

    34. Chapter 5 - Agenda

    35. Uniform Distribution

    36. Binomial Distribution

    37. Poisson Distribution

    38. Normal Distribution Part 1

    39. Normal Distribution Part 2

    40. Skewness

    41. Kurtosis

    42. Calculating Probability with Z-Score

    43. Z-Score Calculation Table

    44. Example

    45. Chapter 6 Agenda

    46. Correlation vs Covariance

    47. Covariance

    48. Correlation

    49. Chapter 7 - Agenda

    50. Hypothesis Testing

    51. Tailed Tests

    52. What is p-value?

    53. Types of Tests

    54. T Test

    55. Z Test

    56. ANOVA

    57. Chi Square

    58. Correlation

    59. Statistcs Quiz

    1. Course Contents

    2. Installation of MySQL Workbench

    3. Data Architecture - File server vs Client server

    4. Introduction to SQL

    5. Constraints in SQL

    6. Table Basics - DDLs

    7. Table Basics - DQLs

    8. Table Basics - DMLs

    9. Joins in SQL

    10. Data Import & Export

    11. Aggregation Functions

    12. String Functions

    13. Date Time Functions

    14. Regular Expressions

    15. Nested Queries

    16. Views

    17. Stored Procedures

    18. Windows Function

    19. SQL-Python connectivity

    20. SQL Quiz

    1. Course Contents

    2. Pre-defined Functions

    3. Datetime Functions

    4. String Functions

    5. Mathematical Functions

    6. Lookup (Hlookup,Vlookup)

    7. Logical & Error Functions

    8. Statistical Functions

    9. Images in Excel

    10. Excel Formatting

    11. Custom Formatting

    12. Conditional Formatting

    13. Charts in Excel

    14. Data Analysis using Excel

    15. Pivot Tables

    16. Dashboarding in Excel

    17. Others

    18. Excel Quiz

About this course

  • ₹4,999.00
  • 278 lessons
  • 45.5 hours of video content