Data Analytics with AI – 251122

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Course Content

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Welcome to TechVidvan

Important Note

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Video – Introduction to Data Science 251122

Notes – Data Science Introduction

Data Science Interview Questions – Introduction

Notes – Data Science History

Notes – Data Science Case Studies in Industry

Notes – Data Science Applications in Real World

Notes – How to Build a Career in Data Science

Notes – Why Data Science is in Demand

Notes – Career Opportunities in Data Science

Notes – Required Skill Set to become a Data Scientist

Notes – Learning Roadmap of Data Science

Notes – Salary Trends & Career Growth in Data Science

Notes – Future of Data Science

Video – Introduction to Data Science Part – 2 251122

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Video – EDA Part – 1 251122

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

Video – EDA Part – 2 251122

Notes – Data Cleaning Essentials in Data Science

Notes – Business Insights from EDA in Data Science

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Video – Linear Regression Part – 1 251122

Notes – Introduction to Regression

Notes – Regression Real-World Use Cases

Notes – Types of Regression Problem

Notes – Linear Regression

Notes – Common Challenges with Regression

Notes – Regression Industry Applications

Video – Deep Dive into Regression

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Video – Label & Ordinal Encoding in ML 251122

Notes – Label Encoding vs One-Hot Encoding

Video – Metric Evaluation in Regression ML 251122

Notes – Evaluation Metrics in Data Science

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Video – Playing with ML Models 251122

Video – Metrics Evaluation in ML Part-2 251122

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Video – Decision Tree Classifier Part-1 251122

Notes – Introduction to Decision Tree

Video – Cross Validation in ML 251122

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Video – Random Forest Algorithm in ML 251122

Video – Random Forest Algorithm Part-2 in ML 251122

Notes – Introduction to Random Forest

Notes – Random Forest Real-World Applications

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Video – Gradient Boosting Algorithm in ML 251122

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Video – Xgboost in ML 251122

Video – Xgboost in ML Part-2 251122

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Video – Unsupervised in ML 251122

Notes – What is Unsupervised Learning?

Data Science Interview Questions – What is Unsupervised Learning?

Notes – Supervised vs Unsupervised Learning

Data Science Interview Questions – Supervised vs Unsupervised Learning

Notes – Where to use Unsupervised Learning

Notes – Application of Unsupervised Learning

Notes – Real world use cases of Unsupervised learnering

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Video – K-means Clustering in ML 260214260110

Notes – K-means Clustering

Notes – K-means Clustering Real-world industry use cases

Notes – Elbow Method in K-means Clustering

Data Science Interview Questions – K-means Clustering

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Video – Dimensionality Reduction in ML 260214260110

Notes – Dimensionality Reduction in Data Science

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Video – Gen AI & Agentic AI 260214260110

Notes – Gen AI

Notes – Agentic AI