Sachith Info Solutions

About Artificial Intelligence Training

Artificial Intelligence (AI) has a long history but is still properly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI such as Data Science, Machine Learning, Deep Learning, Statistics, Artificial Neural Networks, Restricted Boltzmann Machine (RBM) and Tensorflow with Python. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination. This Artificial Intelligence course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is going to apply.

Introduction to Data Science Deep Learning & Artificial Intelligence

Introduction to Deep Learning & AI

Deep Learning: A revolution in Artificial Intelligence

What is Deep Learning?

What is Machine Learning?
Analytics vs Data Science

 Data

Big Data

Data Science Deep Dive

Python

Operators and Keywords for Sequences

Numpy & Pandas

Deep Dive – Functions & Classes & Oops

Statistics

Machine Learning, Deep Learning & AI using Python

Introduction

 Clustering

Implementing Association rule mining

Understanding Process flow of Supervised Learning Techniques

Decision Tree Classifier

Random Forest Classifier

Naive Bayes Classifier.

Project Discussion

Problem Statement and Analysis

Linear Regression

Logistic Regression

Support Vector Machines

Time Series Analysis

Machine Learning Project

Machine learning algorithms Python

Feature Selection and Pre-processing

Which Algorithms perform best

Model selection cross validation score

Text Mining& NLP

PySpark and MLLib

Deep Learning & AI using Python

Deep Learning & AI

Introduction to Artificial Neural Networks

Convolutional Neural Networks

What are RNNs – Introduction to RNNs

Restricted Boltzmann Machine (RBM) and Autoencoders

Tensorflow with Python

Building Neural Networks using

Tensorflow

Deep Learning using

Tensorflow

Transfer Learning using

Keras and TFLearn