PG Certification in Machine Learning

Linux for Data Science, Python Foundations, Machine Learning Prerequisites, Getting Started with SQL, StatisticsFoundations.

Python with Data Science- PySpark, Python, NumPy, SciPy, Matplotlib, Pandas, Python script, Python variables.

Introduction to Machine Learning, Supervised Learning - Classification, Supervised Learning - Classification II, Unsupervised Learning - Clustering, Recommendation System, Machine Learning, ML Deployment in Cloud.

Introduction to Deep Learning, Getting started with Tensorflow 2.0 with Tensor Board, Image Classification using CNN, TensorFlow Hub for Object Detection using Faster RCNN, Tensorflow for Deployment, Convolutional Neural Network, Recurrent Neural Network.

Introduction to NLP with Spacy, Analyzing and Segregating the News Headlines, Building a Resume Classifier, Building an Intent-Based RASA Chatbot, NLP in Production, Encoder-Decoder Network for Neural Machine Translation, Recent Innovations in Language Models.

Statistical Foundations, Probability, Inferential Statistics, Regression, Predictive Analytics.

Doubt Clearing Session + End Course Test, Apply your knowledge of data science and Machine learning to a real-life scenario.