Overview

The program will provide trainees with exposure to and expertise in all the major techniques in AI, covering both the algorithmic/machine learning aspect and data/application engineering:

Understand and use advanced data analytics techniques

Understand and use advanced machine learning techniques

Apply and implement decision and classification techniques

Design advanced machine learning systems and use them to solve classification, prediction, and anomaly detection problems with Phyton language


Who Should Attend

Those who have technical and engineering degrees.


Outline

Day 1

Advanced Classification
Classification Algorithms
Focus on Metric Representation and Dimensionality Reduction
Metric Representation
Dimensionality Reduction Techniques

Day 2

Focus on Clustering
Refresh on K-Means Clustering Algorithms and Its Variants
Clustering Quality Metrics
The Expectation Maximization (EM) Algorithm

Day 3

Focus on Statistical Estimates
Introduction to Big Data IV
Estimate by Maximum Likelihood methods

Day 4

Advanced Deep Learning Models
Adversarial Paradigm
Focus on Privacy

Day 5

Intro to Python
Intro to R
Use Python SDK for ANN training

Day 6

Intro to Libraries
Use Tensorflow for ANN training

Day 7

Use Python SDK for Deep Learner training
Advanced Tensorflow