Data Science & AI Training Modules

We’ve covered complete Data Science concepts including tools like Python, R Prog, R Studio, Keras, Jupyter, PyTorch, Tensorflow, Spyder, NumPy, Pandas, and Scipy in this module.

• CRISP – DM - Project Management Methodology
• Exploratory Data Analytics (EDA) / Descriptive Analytics
• Statistical Data Business Intelligence and Data Visualization
• Plots & Inferential Statistics
• Probability Distributions (Continuous & Discrete)
• Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests
• Data Mining Supervised Learning – Linear Regression, OLS
• Predictive Modelling – Multiple Linear Regression
• Lasso and Ridge Regressions
• Logistic Regression – Binary Value Prediction, MLE
• Multinomial Regression
• Advanced Regression for Count Data
• Machine Learning - k -NN Classifier
• Decision Tree & Random Forest
• Ensemble Techniques - Bagging and Boosting
• Extreme Gradient Boosting (XGB)
• Text Mining and Natural Language Processing (NLP)
• Machine Learning Classifier Technique - Naive Bayes
• Introduction to Perceptron and Multilayer Perceptron
• Building Blocks of Neural Network - ANN
• Deep Learning - CNN, RNN
• Kernel Method - SVM
• Data Mining Unsupervised Learning – Clustering
• Data Mining Unsupervised Learning - Dimension Reduction (PCA)
• Data Mining Unsupervised Learning - Association Rules
• Recommendation Engine
• Network Analytics
• Survival Analytics
• Forecasting/Time Series – Model-Driven Algorithms
• Forecasting/Time Series - Data-Driven Algorithms
• Auto Machine Learning (Auto ML)
• Auto Machine Learning Tree-Based Pipeline Optimization Tool (AutoML TPOT)
• Introduction to Artificial Intelligence and Deep learning
• Python Libraries - TensorFlow, PyTorch, Keras, OpenCV
• Machine Learning Primer
• Mathematical Foundations
• Deep Learning Primer
• Perceptron Algorithm and Back Propagation Neural Network Algorithm
• Artificial Neural Network (ANN), Multilayer Perceptron (MLP)
• Convolution Neural Networks - CNN
• Computer Vision - Self-Driving Cars (SDCs)
• Recurrent Neural Network - RNN
• CNN + RNN Variants, R-CNN & YOLO Models
• LSTM & GRUs - Bidirectional & Deep Bidirectional
• Transformers, BERT, GPT3 & Transformer Variants
• Autoencoders, Variational Autoencoders, RBM
• Deep Belief Networks (DBNs)
• Generative Adversarial Networks - GAN
• Super Resolution GAN
• Reinforcement Learning and Q-learning
• Speech Recognition
• Automatic Text Generation and Chatbot
• Auto Artificial intelligence (Auto AI)
• Explainable Artificial Intelligence (XAI)
• AutoKeras for Artificial Intelligence

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