Artificial Intelligence Training in Chennai

Are you seeking exceptional AI Training? In Chennai, BITA Academy provides Artificial Intelligence Training. AI isn’t just for engineers. If you would like your business to improve its use of AI, this is the training to recommend to everyone, particularly non-technical colleagues. It teaches you to think and learn via a computer or machine. AI Programming teaches you to collect data and apply rules to complete a task.

What is Artificial Intelligence?

Artificial intelligence (AI) is a capability of a computer or a robot operated by a computer to do tasks that usually require human intelligence and insight. Although no AI can accomplish the full range of tasks an ordinary human can, some AIs can match humans in specific skills.

Importance of Learning Artificial Intelligence

The primary purpose of artificial intelligence is to train the machine to think and act appropriately. Artificial intelligence technology is only achievable in real time because of the integration of Data Science and Machine Learning. Machine Learning is a statistical technique for exploring data, and in our Artificial Intelligence Training in Chennai, you will learn the process and tricks of how machines anticipate the future. 

Deep Learning is a subtype of machine learning that produces architecture known as Multi Neural Network Architecture. Deep Learning’s primary goal is to emulate the human brain, allowing machines to think like humans.

Our AI Courses in Chennai will teach you how artificial intelligence works and the skills required to use it. An artificial neural network is a type of machine learning in which interconnected units interpret data by responding to external inputs. Anyone interested in learning Artificial intelligence Training in Chennai should focus on the following subjects. 

• Machine Learning
• Neural Network
• Cognitive Computing
• Deep Learning
• Natural Language Processing (NLP) 

Syllabus for Artificial Intelligence Training in Chennai

Module 1: Introduction to Data Science

• What is Data Science?

• What is Machine Learning?

• Do you know what is Deep Learning?

• What is AI?

• Data Analytics & its types

Module 2: Introduction to Python

• What is Python?

• Why Python?

• How to install Python?

• Python IDEs

• Jupyter Notebook Overview

Module 3: Python Basics

• Python Basic Data types

• Lists

• Slicing

• IF statements

• Loops

• Dictionaries

• Tuples

• Functions

• Array

• Selection by position and Labels

Module 4: Python Packages

• Pandas

• Numpy

• Sci-kit Learn

• Mat-plot library

Module 5: Import Data

• How to read CSV files?

• How to save in Python data?

• Do you know how to load Python data objects?

• How to write data to csv file?

Module 6: Manipulate Data

• How to select rows/observations?

• Do you know to round Number?

• How to select columns/fields?

• Merge data

• Deep Dive on Data aggregation

• Deep Dive on Data munging techniques

Module 7: Statistics Basics

• Central Tendency

• Mean

• Median

• Mode

• Deep Dive on Skewness

• Normal Distribution

• What does it mean by probability?

• Types of Probability

• ODDS Ratio

• Standard Deviation

• Data deviation & distribution

• Variance

• Bias variance Trade off

• What is Underfitting?

• What is Overfitting?

• Distance metrics

• Deep Dive on Euclidean Distance

• Deep Dive on Manhattan Distance

• Outlier analysis

• What is an Outlier?

• InterQuartile Range

• Box and whisker plot

• Upper Whisker

• Lower Whisker

• Scatter plot

• Cook’s Distance

• Missing Value treatment

• What is a NA?

• What do you know about Central Imputation?

• Deep Dive on KNN imputation

• What do you know about Dummification?

• Correlation

• Deep Dive on Pearson correlation

• Positive and Negative correlation

Module 8: Error Metrics

• Classification

• Confusion Matrix

• Precision

• Recall

• Specificity

• F1 Score

• Regression

• MSE

• RMSE

• MAPE

Module 9: Machine Learning

• Supervised Learning

• Deep Dive on Linear Regression

• What do you know about Linear Equation?

• Slope

• Intercept

• R square value

• Logistic regression

• ODDS ratio

• How to find Probability of success?

• How to find Probability of failure Bias Variance Tradeoff?

• ROC curve

• Deep Dive on Bias Variance Tradeoff

Module 10: Unsupervised Learning

• K-Means

• K-Means ++

• Deep Dive on Hierarchical Clustering

Module 10: SVM

• Support Vectors

• Hyperplanes

• 2-D Case

• Deep Dive on Linear Hyperplane

• What do you know about SVM Kernel?

• Linear

• Radial

• What do you know about Polynomial?

Module 11: Other Machine Learning algorithms

• K – Nearest Neighbour

• Naïve Bayes Classifier

• Decision Tree – CART

• Decision Tree – C50

• Random Forest

Module 12: Artificial Intelligence

• AI Introduction

• Perceptron

• Multi-Layer perceptron

• Markov Decision Process

• Logical Agent and First Order Logic

• Look Around AI Applications

Module 13: Deep Learning Algorithms

• CNN – Convolutional Neural Network 

• RNN – Recurrent Neural Network 

• ANN – Artificial Neural Network

Module 14: Natural Language Processing

• NLP – An Overview

• Text Pre-processing

• Noise Removal

• Lexicon Normalization

• Lemmatization

• Stemming

• Object Standardization

Module 15: Text to Features (Feature Engineering)

• Deep Dive on Syntactical Parsing

• Dependency Grammar

• Part of Speech Tagging

• What do you know about Entity Parsing?

• Named Entity Recognition

• Topic Modelling

• N-Grams

• TF – IDF

• Frequency / Density Features

Module 16: NLP Task

• Text Classification

• Text Matching

• What do you know about Levenshtein Distance?

• Deep Dive on Phonetic Matching

• What do you know about Flexible String Matching?