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Cohort 148 - (Da/Ds/GenAI - SS)
₹100,000
one-time purchase
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Course content
22 sections | 42 lessons
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1 Lessons
1. Introduction to Data Analytics 2. Introduction to Python
2 Lessons
1. Python Installation 2. Using Jupyter 3. Basic Python Programming 3. Introduction to Excel formulae
2 Lessons
1. Excel formula, Pivot table, VLOOKUP, XLOOKUP, Creating dashboard, slicer, charts 2. Python: Variables, f-string
2 Lessons
1. Excel: Project Work in class, Assignment 1 2. Python: Basic data types, operators in Python
2 Lessons
1. Python: Conditions, nested condition and introduction to loops
2 Lessons
30th May
1 Lessons
31st May
2 Lessons
1. List example, Stack and Queue implementation using List 2. Tuples 3. Dictionary with examples
2 Lessons
1. Sets in Python 2. Function arguments, types of arguments
2 Lessons
14 June
2 Lessons
1. Keys in DB 2. Relationships 3. Designing tables and columns 4. ER Diagrams 5. Datatypes in MYSQL 6. SQL Commands
2 Lessons
1. CREATE, ALTER, RENAME, DROP Table 2. INSERT INTO, DELETE FROM, UPDATE Tables
2 Lessons
1. Multiple inserts 2. insert by importing using Import wizard and import query 3. Select: Distinct, where, Like, In, Between, Order By 4. Joins in SQL
2 Lessons
1. Aggregate Functions 2. Group By 3. Order By 4. Having 5. Limit & Offset
2 Lessons
1. DML - Update, Delete 2. DDL: Truncate 3. Windows Functions in MYSQL 4. Normalization 5. Dimensional Modelling 6. Data Analysis and Data Wrangling 7. Database Admin 8. Describe and Show commands 9. Assignments - Python and SQL Assignment 2 10. Projects to Practice
2 Lessons
SQL: Temporary table, VIEWS, Stored Procedures 2. Statics: Types of data, Descriptive Stats (Measure of central tendency & Measure of variability)
2 Lessons
Introduction to Data Analytics approach
2 Lessons
One Variable Numeric One Variable Categorical Two Variables: Numeric & Numeric Two Variables: Numeric & Categorical Two Variables: Categorical & Categorical
2 Lessons
1. Visualization: Box Plot 2. Statistics test: ANOVA and Chi Square test 3. Normal distribution
2 Lessons
1. Descriptive stats: Skewness, Kurtosis, Covariance 2. Inferential stats: p value 3. Probability Distribution
2 Lessons
Numpy: Complete Tutorial
2 Lessons
