Available Courses
Data Science & Machine Learning
Python For AI & ML
- Python Basics
- Python Functions, Packages & Routines Probability
- Jupyter Notebook – Installation & Function
- Pandas, NumPy, Matplotlib, Seaborn
- Working with Data Structures, Arrays, Vectors& Data Frames
Statistical Learning
- Descriptive Statistics
- Probability & Conditional
- Hypothesis Testing
- Probability Distribution – Types of distribution –binomial, Poisson & normal distribution
Supervised Learning
- Multiple Variable Linear Regression
- Logistic Regression
- Naïve Bayes Classifiers
- Multiple Regression
- K-NN Classification
- Support Vector Machines
Unsupervised Learning
- K-Means Clustering
- High-Dimensional Clustering
- Hierarchical Clustering
- Dimension Reduction-PCA
Ensemble Techniques
- Decision Trees
- Bagging
- Random Forests
- Boosting system
Recommendation Systems
- Introduction to recommendation system
- Popularity based model
- Hybrid Models
- Content Based recommendation
- Collaborative filtering
Neural Network Basics
- Gradient Descent
- Batch Normalization
- Hyper Parameter tuning
- Activation and Loss function
- Deep Neural Networks
- Intro to Perceptron & Neural Networks
Computer Vision
- Intro to Convolutional Neural Networks
- Convolution, Pooling, Padding & Mechanism
- Transfer Learning
- Forward propagation & Back propagation for CNNs
- CNN architectures like AlexNet, VGGNet, InceptionNet & ResNet
Statistical NLP
- Bag of Words Model
- POS Tagging
- Tokenization
- Word Vectorizer
- TF-IDF
- Named Entity Recognition
- Stop Words
Advanced Computer Vision
- Semantic Segmentation
- Siamese Networks
- YOLO
- Object & face recognition
Sequential NLP
- Intro to Sequential data Adversarial Net Intro
- Vanishing & Exploding gradients in RNNs
- LSTMs
- GRUs – Gated recurrent unit
- Case study: Sentimental analysis
- RNNs and its mechanisms
- Time series analysis
- LSTMs with attention mechanism
- Case study: Machine Translation
GANs
- GAN - Generative
- How GANs work?
- Auto Encoders
- Applications of GANs
Languages & Tools
- Python
- Python ML library scikit-learn
- NLP library NLTK
- Keras
- Data Libraries like Pandas, Numpy, Scipy
- Python visualization library Matplotlib
- Tensor Flow
- Seaborn
Reinforcement Learning
- Value based methods Q-Learning
- Policy based methods
