Advanced Machine Learning & Deep Learning.
Become a Machine Learning Engineer
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Our 3 month intensive online program has been carefully curated keeping in mind the current industry demands. It is to be noted that the lecture are not pre recorded. It’s a live interactive session and live training conducted with one on one mentoring.
Watch this demo of a Self driving Car
Key Features
Programming language & tools covered
Python, Anaconda, Jupyter Notebook, TensorFlow, Keras, Scikit-Learn, OpenCV
Key Features
Job roles capabilities
Data scientist, Data science engineer, Machine learning engineer, Data analyst, Machine earning consultant.
Key Features
Top skills you will learn
Python, Language modelling, Predictive Analysis and Statistics, Deep learning, CNN, RNN, LSTMs, Computer Vision, Deep Reinforcement Learning.
High Level Deep Learning Framework
Low Level Deep Learning Framework
Jupyter Notebook
Programming
Language
Best-in-class content by leading faculty and industry leaders in the
form of
videos, cases and projects, assignments and live sessions.
Prediction of house prices based on factors like population, literacy in the area, price per sq. feet, etc. using Machine Learning.
Solve the problems in traditional Q-learning Algorithm with Deep Q-Networksby using TensorFlow & Keras. In this project we will be building our own Flappy Bird game with python and then build a smarter agent that can beat your High score in Flappy Bird.
Predicting ad click--through rates (CTR) is a massive-scale learning problem that is central to the multi-billion dollar online advertising industry. We will be trying to build Machine Learning model to predict the CTR for an online E-commerce platform.
To get familiar with python as a programming language, we will be using it to develop a simple Rock-Paper-scissor game with simple python coding
Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions.
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NO COST EMI OPTION AVAILABLE
Please read through the following Prerequisites sections before beginning this Course, to ensure you are prepared to complete all the modules
