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AIMLDS – 251122

About the Course

Welcome to TechVidvan

Important Note

Getting Started with Data Science Sample Lesson

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

Exploratory Data Analysis 251122

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

Regression in Machine Learning 251122

Video – Linear Regression Part – 1 251122

Notes – Introduction to Regression

Data Science Interview Question – Introduction to Regression

Notes – Regression Real-World Use Cases

Notes – Types of Regression Problem

Notes – Linear Regression

Data Science Interview Question – Linear Regression

Notes – Common Challenges with Regression

Notes – Regression Industry Applications

Video – Deep Dive into Regression

Encoding in Machine Learning 251122

Video – Label & Ordinal Encoding in ML 251122

Video – Metric Evaluation in Regression ML 251122

Machine Learning Models 251122

Video – Playing with ML Models 251122

Video – Metrics Evaluation in ML Part-2 251122

Decision Tree 251122

Video – Decision Tree Classifier Part-1 251122

Video – Cross Validation in ML 251122

Random Forest Algorithm 251122

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

Data Science Interview Questions – Introduction to Random Forest

Gradient Boosting in ML 251122

Video – Gradient Boosting Algorithm in ML 251122

Notes – Gradient Boosting in ML

XGBoost Algorithm in ML 251122

Video – Xgboost in ML 251122

Video – Xgboost in ML Part-2 251122

Notes – XGBoost in ML

Unsupervised Learning in ML 251122

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

K-means Clustering in ML 260214260110

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

Dimensionality Reduction in ML 260214260110

Video – Dimensionality Reduction in ML 260214260110

Notes – Dimensionality Reduction in Data Science

Start with Deep Learning 260214260110

Video – Working on Deep Learning 260214260110

Notes – Deep Learning Introduction

Data Science Interview Questions – Deep Learning Introduction

Notes – Deep Learning vs Machine Learning

Data Science Interview Questions – Deep Learning vs Machine Learning

Notes – Deep Learning Case Studies in Industry

Notes – Why Deep Learning?

Notes – Need for Deep Learning in Industry

Notes – Why Deep Learning is in Demand?

Notes – Key Deep Learning Terminologies

CNN in Deep Learning 260214260110

Video – CNN in DL 260214260110

Notes – CNN (Convolutional Neural Network)

Data Science Interview Questions – CNN

Video – CNN in DL Part-2 260214260110

RNN & LSTM in Deep Learning 260214260110

Video – RNN & LSTM in DL 260214260110

Notes – RNN in Data Science

Data Science Interview Questions – RNN

Notes – LSTM in Deep Learning

Notes – LSTM Applications and Use Cases

Data Science Interview Questions – LSTM in Deep Learning

Notes – RNN vs LSTM

Video – LSTM Part-2 in DL 260214260110

Gen AI for Data Science 260214260110

Video – Gen AI & Agentic AI 260214260110

Notes – Gen AI

Notes – Agentic AI

DSML Projects

Data Engineering 260214260110

Video – Data Engineering 260214260110

Video – Data Engineering Part-2 260214260110

Notes – Data Engineering in Data Science

Data Science Interview Questions – Data Engineering

Notes – Big Data in Data Science

Data Science Interview Questions – Big Data

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Video – Introduction to Data Science Part – 2 251122

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AIMLDS – 251122
Getting Started with Data Science
Video – Introduction to Data Science Part – 2 251122

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