Price: INR 55,000
- Other Location: J. P. Nagar - Bangalore
- Duration / Course length: 8 Days
- Starting Date: Enquire About It
- Timings: Enquire
Course details
- Foundations and Tools
- General Approach to Machine Learning
- Review of Mathematical Concepts
- iPython, Numpy, Matplotlib Tutorial
- Understanding Data and Features
- Understanding & Exploring Data
- Feature Engineering
- Visualisation Techniques
- Matplotlib Visualisations
- Non-Parametric Models
- Nearest Neighbour Models
- Decision Trees
- Random Forests
- Scikit Learn Tutorial
- Probabilistic Graphical Models
- Naive Bayes Models
- Bayesian Networks
- Conditional Random Fields
- Tutorial: NLTK/spaCy for NLP
- Feedforward Neural Networks
- Single Layer Neural Network
- Multilayer Neural Network
- Introduction to Keras
- Deep Learning Introduction
- Deep Learning Overview
- Convolutional Neural Networks
- Recurrent Neural Networks
- Implementing Deep Neural Networks in Keras
- Models for other Common Tasks
- Clustering Models
- Recommender Models
- Learning to Rank Models
- Anomaly Detection
Eligibility / Requirements
- Degree in Engineering
- No prior knowledge of Machine Learning required
- Should be comfortable coding in Python
- Elementary knowledge of matrices, probability and differential calculus is preferred
Course Location
About The School of AI
The School of AI has been conceptualized and started by Mr. Ramprakash H. Ram holds a B. Tech degree in Computer Science from IIT Madras. As an entrepreneur, Machine Learning researcher, and a hands-on practitioner for more than fifteen years, he has built and shipped several ML based technologies like Quillpad, for which he was recognized among top twenty innovators in India by MIT TR 35. Teaching is his passion and his teaching pedagogy focuses on "HOW" a concept is taught in a way that his students can understand, imbibe and relate to it in any sphere of life. We have launched our first course in Bangalore under The School of AI banner - "Machine Learning for Hands-On Engineers", which comprises 8 classroom sessions spanning over 2 months (classes every Sunday), along with various practical assignments and hands-on activities to promote efficient learning. See all The School of AI coursesEnquire about this course
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