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AIDSML – 260214
Getting Started 260214
Sample Lesson
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Getting Started 260214
6 Topics
Video – DS Introduction 260214
Notes – Data Science Introduction
Notes – Data Science History
Notes – Data Science Case Studies in Industry
Notes – Data Science Applications in Real World
Data Science Interview Questions – Introduction
Exploratory Data Analysis 260214
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Exploratory Data Analysis 260214
4 Topics
Video – EDA Part-1 in DS 260214
Video – EDA Part-2 in DS 260214
Notes – Exploratory Data Analysis
Interview Questions – Exploratory Data Analysis
Regression in ML 260214
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Regression in ML 260214
6 Topics
Video – Regression Part-1 in ML 260214
Notes – Introduction to Regression
Notes – Regression Real-World Use Cases
Data Science Interview Question – Introduction to Regression
Video – Regression Projects in ML 260214260110
Regression Assignments
Classification in ML 260214260110
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Classification in ML 260214260110
6 Topics
Video – Classification in ML Part-1 260214260110
Notes – What is Classification?
Data Science Interview Questions – What is Classification?
Notes – Classification Real-World Applications
Notes – Regression vs. Classification
Data Science Interview Questions – Regression vs. Classification
Logistic Regression in ML 260214260110
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Logistic Regression in ML 260214260110
4 Topics
Video – Logistic Regression Part-1 in ML 260214260110
Video – Logistic Regression Part-2 in ML 260214260110
Notes – Logistic Regression
Data Science Interview Questions – Logistic Regression
K-Nearest Neighbors in ML 260214260110
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K-Nearest Neighbors in ML 260214260110
6 Topics
Video – KNN in ML 260214260110
Notes – What is k-NN?
Data Science Interview Questions – What is k-NN?
Notes – How k-NN Works
Data Science Interview Questions – How k-NN Works
Notes – KNN Real-World Applications
Decision Tree in ML 260214260110
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Decision Tree in ML 260214260110
12 Topics
Video – Decision Tree in ML 260214260110
Notes – Introduction to Decision Tree
Data Science Interview Questions – Introduction to Decision Tree
Notes – Decision Tree Real-World Use Cases
Video – Decision Tree Part-2 in ML 260214260110
Notes – Types of Decision Trees
Notes – Components of a Decision Tree
Notes – Decision Tree Splitting Criteria
Notes – Gini Impurity in Decision Tree
Notes – Entropy & Information Gain in Decision Tree
Notes – Advantages and Limitations of Decision Tree
Notes – Pre-Pruning and Post-Pruning in Decision Tree
Random Forest in ML 260214260110
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Random Forest in ML 260214260110
10 Topics
Video – Random Forest in ML 260214260110
Notes – Introduction to Random Forest
Data Science Interview Questions – Introduction to Random Forest
Notes – Why use Random Forest over a Single Tree?
Notes – Random Forest Real-World Applications
Notes – Concept Behind Random Forest
Notes – How Random Forest Works
Notes – Random Forest Hyperparameters
Notes – Random Forest Advantages and Limitations
Notes – Random Forest Use Cases
Unsupervised Learning in ML 260214260110
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Unsupervised Learning in ML 260214260110
9 Topics
Video – Unsupervised Learning in ML 260214260110
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
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K-means Clustering in ML 260214260110
5 Topics
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
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Dimensionality Reduction in ML 260214260110
2 Topics
Video – Dimensionality Reduction in ML 260214260110
Notes – Dimensionality Reduction in Data Science
Start with Deep Learning 260214260110
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Start with Deep Learning 260214260110
10 Topics
Video – Working on Deep Learning 260214260110
Notes – 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
Data Science Interview Questions – Deep Learning Introduction
CNN in Deep Learning 260214260110
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CNN in Deep Learning 260214260110
4 Topics
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
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RNN & LSTM in Deep Learning 260214260110
8 Topics
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
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Gen AI for Data Science 260214260110
3 Topics
Video – Gen AI & Agentic AI 260214260110
Notes – Gen AI
Notes – Agentic AI
DSML Projects
Data Engineering 260214260110
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Data Engineering 260214260110
6 Topics
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
Next Topic
Getting Started 260214
LMS
AIDSML – 260214
Getting Started 260214
Lesson Content
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Video – DS Introduction 260214
Notes – Data Science Introduction
Notes – Data Science History
Notes – Data Science Case Studies in Industry
Notes – Data Science Applications in Real World
Data Science Interview Questions – Introduction
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