Python with Data Science (AI & ML)
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Python with Data Science (AI & ML)
Time: Sep 29, 2025 09:30 PM Eastern Time (US and Canada)
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Python for Data Science: Introduction
Python for Data Science: Data Structures (List, Tuple, Dictionary, Set)
Python for Data Science: Functions
Python for Data Science: NumPy
Python for Data Science: Matplotlib
Python for Data Science: Advanced Visualization with Seaborn
Python for Data Science: Data Manipulation with Pandas
Working with SQL in Data Science
Sample Interview Questions
Plotting for exploratory data analysis (EDA)
Linear Algebra
Probability and Statistics
Dimensionality reduction and Visualization: PCA(principal component analysis)
Dimensionality reduction and Visualization: (t·SNE}T-distributed Stochastic Neighborhood Embedding
Statistical Testing
Sample Interview Questions
Introduction to Machine Learning
Performance measurement of models
Classification And Regression Models: K Nearest Neighbors
Naive Baye’s
Linear Regression
Logistic Regression
Classification algorithms in various situations
Real world problem: Predict rating on given product reviews on Amazon
Sample Interview Questions
Unsupervised learning/Clustering
Hierarchical clusteringTechnique
DBSCAN – Density-Based Clustering
Recommender Systems and Matrix Factorization
Interview Questions on Recommender Systems and Matrix Factorization
Case Study 6: Amazon fashion discovery engine (Content based recommendation)
Case Study 7: Netflix Movie Recommendation System(Collaborative based recommendation)
Case Study 8: Music Recommendation system
Sample Interview Questions
Deep Learning: Neural Networks
Deep Learning: Deep Multilayer perceptron's
Deep Learning: Tensor Flow and Keras
Deep Learning: Convolutional Neural Nets
Deep Learning: Long Short-term memory (LSTMs)
Deep Learning: Generative Adversarial Networks(GANS) Encoder-Decoder Models
Deep Learning: Image Segmentation
Deep learning: Object Detection
OpenCV using Python
Interview Questions on Deep Learning
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