AIDA – 260509

AIDA – 260509

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Course Curriculum:

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Course Content

Lesson Content

0% Complete 0/2 Steps

Welcome to TechVidvan

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Video – Introduction to AI ML 260509

Video – AI ML Part-2 260509

Notes – AI Introduction

Notes – ML Introduction

Lesson Content

0% Complete 0/5 Steps

Video – Pandas 260509

Notes – Introduction to Pandas

Pandas Interview Questions – Introduction

Notes – Series in Pandas

Notes – DataFrame in Pandas

Lesson Content

0% Complete 0/13 Steps

Video – EDA Part-1 260509

Video – EDA Part-2 260509

Notes – Exploratory Data Analysis

Interview Questions – Exploratory Data Analysis

Notes – Numerical vs Categorical Data in Data Science

Notes – Continuous vs. Discrete Data in Data Science

Notes – Feature Engineering in Data Science

Notes – Handling Missing Values in Data Science

Notes – Handling Outliers in Data Science

Notes – Univariate, Bivariate, Multivariate Analysis in Data Science

Notes – Correlation in Data Science

Notes – Data Cleaning Essentials in Data Science

Notes – Business Insights from EDA in Data Science

Lesson Content

0% Complete 0/11 Steps

Video – Linear Regression 260509

Notes – Introduction to Regression

Data Science Interview Question – Introduction to Regression

Notes – Regression Real-World Use Cases

Notes – Linear Regression

Data Science Interview Question – Linear Regression

Video – Regression Part-1 260509

Video – Regression Part-2 260509

Notes – Types of Regression Problem

Notes – Common Challenges with Regression

Notes – Regression Industry Applications

Lesson Content

0% Complete 0/6 Steps

Video – Matplotlib – NumPy – 260509

Video – Logistic Regression – 260509

Video – Logistic Regression part-2 – 260509

Video – KNN – 260509

Video – Decision Tree – 260509

Video – Decision Tree part-2 – 260509