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Data Analytics with AI – 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
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
Encoding in Machine Learning 251122
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
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
Notes – Introduction to Decision Tree
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
Gradient Boosting in ML 251122
Video – Gradient Boosting Algorithm in ML 251122
XGBoost Algorithm in ML 251122
Video – Xgboost in ML 251122
Video – Xgboost in ML Part-2 251122
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 – Popular Algorithms in 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
Gen AI for Data Science 260214260110
Video – Gen AI & Agentic AI 260214260110
Notes – Gen AI
Notes – Agentic AI
DA Projects
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Video – Introduction to Data Science 251122

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