Course fees
Working Professionals as trainers
Trainers Experience
Student Web Portal
Class Room Infrastructure
Reference Pay
Instalment
Lab Infrastructure
Who are our trainers?
Student’s Ratings
Trust & Credibility
Fees Negotiable?
Best Artificial Intelligence AI in Bangalore & Top Artificial Intelligence AI Course Institute
Artificial Intelligence AI Course in Bangalore
Best Artificial Intelligence AI in Bangalore & Top Artificial
Intelligence AI Course Institute
Are you looking for the best Artificial Intelligence AI Course
in Bangalore?. Our Artificial Intelligence AI Course Institute in Bangalore
will ensure you to understand the Concepts and terminologies of Artificial
Intelligence AI with both Theory and Practicals to get real-time understanding
and Exposure in Learning Artificial Intelligence AI . Our Artificial
Intelligence AI Syllabus and Course Content is crafted by many MNC HR’s and
Experts which is as per current Industry requirements and helps you to be one
step ahead in the Artificial Intelligence AI field compared to other course institutes.
Our Artificial Intelligence AI Trainers are working
professionals with minimum 10+ Years of Expertise in Artificial Intelligence AI
Domain and provide course with real-time projects. To know more about Artificial
Intelligence AI , Book a Free Demo Class today and get an overall idea of what
you are going to learn and scope of doing Artificial Intelligence AI Course as
per current Market Trends. We also Provide Lab Facilities, Mock Interviews,
Resume Preparation and 100% Placement Assistance to get you placed in Artificial
Intelligence AI.
Artificial Intelligence Course Content
Module 1 : Artificial Intelligence
An Introduction to Artificial Intelligence
History of Artificial Intelligence
Future and Market Trends in Artificial Intelligence
Intelligent Agents – Perceive-Reason-Act Loop
Search and Symbolic Search
Constraint-based Reasoning
Simple Adversarial Search (Game-Playing)
Neural Networks and Perceptrons
Understanding Feedforward Networks
Boltzmann Machines and Autoencoders
Exploring Backpropagation
Module 1 : Deep Networks and Structured Knowledge
Deep Networks/Deep Learning
Knowledge-based Reasoning
First-order Logic and Theorem
Rules and Rule-based Reasoning
Studying Blackboard Systems
Structured Knowledge: Frames, Cyc, Conceptual Dependency
Description Logic
Reasoning with Uncertainty
Probability & Certainty-Factors
What are Bayesian Networks?
Understanding Sensor Processing
Module 3: Natural Language Processing
Studying Neural Elements
Convolutional Networks
Recurrent Networks
Long Short-Term Memory (LSTM) Networks
Module 4: Machine Learning and Hacking
Machine learning
Reprise: Deep Learning
Symbolic Approaches and Multiagent Systems
Societal/Ethical Concerns
Hacking and Ethical Concerns
Behaviour and Hacking
Job Displacement & Societal Disruption
Ethics of Deadly AIs
Danger of Displacement of Humanity
Module 5: The future of Artificial Intelligence
Natural Language Processing
Natural Language Processing
Natural Language Processing in Python
Natural Language Processing in R
Studying Deep Learning
Artificial Neural Networks
ANN Intuition
Plan of Attack
Studying the Neuron
The Activation Function
Working of Neural Networks
Exploring Gradient Descent
Stochastic Gradient Descent
Exploring Backpropagation
Module 6: Artificial and Conventional Neural Network
Understanding Artificial Neural Network
Building an ANN
Building Problem Description
Evaluation the ANN
Improving the ANN
Tuning the ANN
Conventional Neural Networks
CNN Intuition
Convolution Operation
ReLU Layer
Pooling and Flattening
Full Connection
Softmax and Cross-Entropy
Building a CNN
Evaluating the CNN
Improving the CNN
Tuning the CNN
Module 7: Recurrent Neural Network
Recurrent Neural Network
RNN Intuition
The Vanishing Gradient Problem
LSTMs and LSTM Variations
Practical Intuition
Building an RNN
Evaluating the RNN
Improving the RNN
Tuning the RNN
Module 8: Self-Organizing Maps
Self-Organizing Maps
SOMs Intuition
Plan of Attack
Working of Self-Organizing Maps
Revisiting K-Means
K-Means Clustering
Reading an Advanced SOM
Building an SOM
Module 9: Boltzmann Machines
Energy-Based Models (EBM)
Restricted Boltzmann Machine
Exploring Contrastive Divergence
Deep Belief Networks
Deep Boltzmann Machines
Building a Boltzmann Machine
Installing Ubuntu on Windows
Installing PyTorch
Module 10: AutoEncoders
AutoEncoders: An Overview
AutoEncoders Intuition
Plan of Attack
Training an AutoEncoder
Overcomplete hidden layers
Sparse Autoencoders
Denoising Autoencoders
Contractive Autoencoders
Stacked Autoencoders
Deep Autoencoders
Module 11: PCA, LDA, and Dimensionality Reduction
Dimensionality Reduction
Principal Component Analysis (PCA)
PCA in Python
PCA in R
Linear Discriminant Analysis (LDA)
LDA in Python
LDA in R
Kernel PCA
Kernel PCA in Python
Kernel PCA in R
Module 12: Model Selection and Boosting
K-Fold Cross Validation in Python
Grid Search in Python
K-Fold Cross Validation in R
Grid Search in R
XGBoost
XGBoost in Python
XGBoost in R
No Interview Questions Found..
Course fees
Working Professionals as trainers
Trainers Experience
Student Web Portal
Class Room Infrastructure
Reference Pay
Instalment
Lab Infrastructure
Who are our trainers?
Student’s Ratings
Trust & Credibility
Fees Negotiable?
Very competitive and affordable.
Yes
Min 7+ Years experience
We have a dedicated students portal
All classrooms are Ventilated with power backups.
We pay Rs 1000 for every student you refer.
Yes its very flexible, you can pay the fees in instalment
We Have Excellent Lab Facility and Provide server access
IT consultants,Solutions Architects, Technical Leads
5 ***** ratings from more than 4000 students
Very High
Definitely yes we understand the financial situation of each student
Really less fees but compromise with the quality
Very Few
Trainers have less exposure to real time work.
None
Very few institutes
None
Very few institutes
None
hire full time trainers with very little experience
Mixed
Moderate.
Very few