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Cohort 136 - (Da/Ds/GenAI/AI - SS)
₹100,000
one-time purchase
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Course content
40 sections | 82 lessons
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Batch link. passcode and updates section
1 Lessons
Introduction to data analytics/science & Python Installation
2 Lessons
1. Python and IDE installation 2. Introduction to Excel
2 Lessons
Analytics using Excel
2 Lessons
1. Excel advanced formulae - class project completions 2. Python: variables, mathematical operations, basic data types, type(), format string
2 Lessons
1. Relational operators 2. Logical operators 3. functions: input(), int(), range() 4. conditions: if, elif, else 5. introduction to for loop
2 Lessons
1. Conditions: Practice Programs 2. Loops: For loop, Nested For loop and While loop
2 Lessons
1. For loop 2. While Loop 3. match-case 4. Mini Project
2 Lessons
* String declaration * String Operations * indexing * string methods Introduction to List
2 Lessons
1. List 2. Tuple 3. Dictionary. 4. Exercises in Lists and Dictionary 5. Assignment 2 (Python -1)
2 Lessons
1. Sets in Python 2. Function tutorial: Arguments (Required, Default, Positional, Keyword, variable length), Return type, doc string 3. Modules
2 Lessons
1. Practice functions in Python 2. Class and objects in Python
3 Lessons
1. PIVOT in excel 2. LAMBDA functions 3. Map(), Filter(), Reduce() in Python lists 4. Exception handling in Python
2 Lessons
1. File Handling in Python 2. Introduction to Database, RDBMS 3. Keys in Database 4. Relationships 5. MYSQL Installation
2 Lessons
SQL Commands * CREATE , DROP Table in SQL
2 Lessons
SQL tutorial * Insert , Update, Truncate * Select session 1
2 Lessons
1. SELECT Commands in SQL - session 2 2. INDEX, VIEWS and TEMPORARY TABLES IN MYSQL
2 Lessons
1. Stored Procedures in MYSQL 2. Statistics: Types of data, Descriptive statistics, Handing data
2 Lessons
1. Statistics- Managing Numerical v Numerical and Categorical v Categorical data analysis
2 Lessons
1. Categorical v Numerical 2. Boxplot 3. ANOVA 4. Quartile, Percentile 5. Identifying Outliers
2 Lessons
Numpy Session 1
3 Lessons
1. Numpy tutorial 2. Pandas basic tutorial 3. matplotlib tutorial
2 Lessons
1. Advanced Pandas discussions with lab 2. Mini Project for Data Analytics 3. Projects for Home Work
3 Lessons
1. Handling missing values using Python (mini project)
2 Lessons
8th February
1 Lessons
1. Power BI Data Analytics Process 2. Data processing steps
2 Lessons
Data Transformation in Power BI
2 Lessons
* Data transformation - 2 * Basic Visualization
2 Lessons
1. Power BI Visualization and editing the various properties 2. Data Modelling 3. Basic DAX operations
2 Lessons
1. Advanced visualization in Power BI 2. Advanced DAX 3. Introduction to Machine Learning
2 Lessons
1. Introduction Machine Learning, examples and life cycle 2. Understanding Data cleaning
2 Lessons
1. Data Preprocessing: Scaling, Encoding, missing values, outliers, feature extraction, feature construction
2 Lessons
1. Regression concept 2. Simple Linear Regression 3. Regression Model evaluation: MAE, MSE, RMSE, R Square 4. Overfitting v Underfitting 5. Multiple Linear Regression
3 Lessons
Regression - Ridge regression and summary of regression analysis. Home work
2 Lessons
Introduction to Classification Model, Logistic Regression
2 Lessons
1. Decision Tree, Random Forest, K Nearest Neighbor 2. ML Assignment 3. Practice Projects
2 Lessons
1. ML: Hierarchical & K_Means clustering 2. Advanced Excel: Covariance, Correlation & Regression
2 Lessons
Advance Excel: Moving Average, What if Analysis, Goal Seek, Data Table, Descriptive statistics Deep Learning: Introduction, ANN
2 Lessons
1. Deep Learning 2. Natural Language Processing (NLP)
2 Lessons
1. Cloud computing 2. Agile methodology 3. streamlit introduction 4. Model deployment (serialization using json) 5. github 6. kaggle & github for more projects
2 Lessons
