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Artificial Intelligence Certification Training

  • Get your AI career started with our Artificial Intelligence training program and gain practical learnings around Deep Learning and Machine Learning, and the clean-coded & effective programming languages.
  • Get equipped with our real-world case studies to qualify the competent AI certifications and level up for the market’s demanding job roles.

Next Class Begins in 4 days - 13 Aug 2020

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Why AI Certification Course?

Some intriguing facts to take up AI Training and certification.

22%

Of the people have reported job satisfaction with their profiles

43%

The rise in the number of students opting for AI training

8,993

AI-related jobs were posted on LinkedIn in October 2019

$100K+

Is the average annual compensation of AI engineers in the USA

16%

The rise in the overall employment of AI engineers in the USA

Do You Know Why Artificial IntelligenceTraining is Necessary to Grow Your Career?

14%

Increase in demand for Artificial Intelligence professionals all across the globe within 2019

Thriving Career Opportunities - What and Where!

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Learn AI capabilities to handle the leading organization’s AI-driven infrastructure!

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IT

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Healthcare & medicine

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Banking &
Finance

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Transportation/Freight

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eCommerce

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Media &
Entertainment

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NPO

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Financial
Services

AI/Machine Learning Engineer

Data Scientist

Business Intelligence Developer

Big Data Engineer/Architect

Instructor-led Live Online Artificial Intelligence Classes


Starting
Duration
Price

13 Aug

WEEKDAY - Filling Fast

8 Weeks

09.00 - 10.30 PM EST

USD 1199

USD 1019

Flat 15% Off

07 Sep

WEEKDAY

8 Weeks

09.00 - 10.30 PM EST

USD 1199

25 Aug

WEEKEND

8 Weeks

08.00 - 11.00 AM EST

USD 1199

15 Oct

WEEKDAY

8 Weeks

09.00 - 10.30 PM EST

USD 1199

05 Nov

WEEKDAY

8 Weeks

09.00 - 10.30 PM EST

USD 1199

USD 839

Flat 30% Off

Early Bird Discount

Easy Installments

Enroll Now and pay Later (on request)

Detail
WEEKDAY - Filling Fast

13 Aug


8 Weeks

09.00 - 10.30 PM EST

USD 1199

USD 1019

Flat 15% Off

Enroll Now
WEEKDAY

07 Sep


8 Weeks

09.00 - 10.30 PM EST

USD 1199

WEEKEND

25 Aug


8 Weeks

08.00 - 11.00 AM EST

USD 1199

WEEKDAY

15 Oct


8 Weeks

09.00 - 10.30 PM EST

USD 1199

WEEKDAY

05 Nov


8 Weeks

09.00 - 10.30 PM EST

USD 1199

USD 839

Flat 30% Off

Early Bird Discount

Enroll Now

Easy Installments

Enroll Now and pay Later (on request)

Not Sure Which Artificial Intelligence Class to Join?  

Best-in-class content by leading faculty & industry leaders in the form of videos and projects, assignments & live sessions.

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Artificial Intelligence Certification Training Course Roadmap

Want to know what all you will be learning in our online course on Artificial Intelligence?

AI Intro, Python for AI & ML, SQL

    • What is AI, Why AI?
    • Programming for Problem Solving
    • Artificial intelligence fundamentals
    • Components of AI
    • Python Overview
    • Important Python features
    • Python installation, Anaconda Python distribution
    • Python Functions and Packages
    • Scikit-Learn for Machine Learning & LNP
    • Working with Data Structures,Arrays,
    • Math Operators and Expressions
    • Vectors & Data Frames
    • Pandas, NumPy, Matplotlib
    • Numpy for Statistical Analysis
    • Matplotlib & Seaborn for Data Visualization
    • Descriptive Statistics
    • Probability & Conditional Probability
    • Probability Distributions
    • Working with Databases
    • How to create a Database instance on Cloud
    • CREATE Table Statement
    • SELECT Statement
    • COUNT, DISTINCT, LIMIT
    • INSERT, UPDATE and DELETE Statements
    • Information and Data Models
    • Types of Relationships
    • Sub-Queries and Nested Selects

Machine Learning: Supervised Learning

    • Introduction to Machine Learning
    • Understanding Supervised Learning.
    • Linear Regression Theory
    • Supervised Learning Regression
    • Linear Regression
    • Multiple Linear Regression
    • Bias-Variance Trade-Off
    • Logistic Regression
    • K-Nearest Neighbors (KNN)
    • Simple Vector Machine (SVM)
    • Decision Trees
    • Bagging
    • Boosting, AdaBoost & XGBoost
    • Naïve Bayes Classifier

Machine Learning: Unsupervised Learning

    • K-Means Clustering
    • Hierarchical Clustering
    • Dimensionality Reduction
    • Linear Discriminant Analysis
    • Time Series Modelling
    • Principal Component Analysis (PCA)
    • Reinforcement Learning
    • Model Comparisons
    • Analysis Considerations
    • Clustering Animals
    • Customer Segmentation
    • Optimal Number of Clusters
    • Cluster Based Incentivization
    • Image Segmentation

Deep Learning with Tensorflow, Keras

    • What is Neural Networks
    • Gradient Descent
    • Perceptron & Neural Networks
    • Batch Normalization
    • Activation and Loss functions
    • Hyper parameter tuning
    • Deep Neural Networks
    • Tensor Flow & Keras for Neural Networks & Deep Learning
    • Understand Neural Networks in Detail
    • PyTorch Tensors
    • PyTorch Autograd
    • Illustrate Multi-Layer Perceptron
    • Backpropagation – Learning Algorithm
    • Understand Backpropagation – Using Neural Network Example
    • MLP Digit-Classifier using TensorFlow
    • Building a multi-layered perceptron for classification

Neural Networks, Convolutional Neural Network,Recurrent Neural Networks

    • Artificial neural networks in Deep Learning
    • Linear & Logistic Regression With Tensorflow
    • Activation Functions
    • Illustrate Perceptron
    • Important Parameters of Perceptron
    • Shallow, Deep neural networks
    • Optimization algorithms
    • Hyper-parameter tuning
    • Batch Normalization and Programming Frameworks
    • Single layer NN & Multilayer NN
    • Back propagation, Dynamic Programming
    • Mathematical Take on NN
    • Function Approximator
    • Kernels, Padding & Strides
    • Convolutional Layer, Max-Pooling
    • CNN Architectures – VGGNet, AlexNet, Inception Network
    • Rnns with back propagation
    • Long short-term memory (lstm)
    • Link with Linear Regression
    • Recurrent Neural Network
    • Backpropagation in RNN.
    • Types of RNN, Architecture of RNN

Natural Language Processing

    • Understanding NLP
    • Stop Words, Tokenization
    • Stemming and lemmatization
    • Bag of Words Model
    • Word Vectorizer
    • POS Tagging
    • Named Entity Recognition
    • Text Pre-processing
    • Topic Modelling
    • Noise Removal
    • Lexicon Normalization, Lemmatization, Stemming
    • Object Standardization
    • Text Classification, Text Matching
    • Levenshtein Distance
    • Phonetic Matching, Flexible String Matching

Artificial Intelligence Certification Training Course Roadmap

  • Want to know what all you be learning? Check it out Now!

    • What is AI, Why AI?
    • History of Artificial Intelligence
    • Future and Market Trends in Artificial Intelligence
    • Programming for Problem Solving
    • Artificial intelligence fundamentals
    • Components of AI
    • Computational mathematics for learning and data analysis
    • Machine learning
    • Human Level Performance
    • Parallel and distributed systems: paradigms and models
    • Intelligent Systems for pattern recognition
    • Python Overview
    • History of Python?
    • Important Python features
    • Python-2 and Python-3 differences
    • Install Python and Environment Setup
    • First Python Program
    • Python Identifiers, Keywords, and Indentation
    • Python Functions and Packages
    • Vectors & Data Frames
    • Pandas, NumPy, Matplotlib
    • Numpy for Statistical Analysis
    • Matplotlib & Seaborn for Data Visualization
    • Descriptive Statistics
    • Probability & Conditional Probability
    • Probability Distributions
    • Data Types, Variables and Keywords
    • Control flow
    • Decision Making
    • Branching and Looping
    • String functions
    • List, Tuple, Dictionary
    • Functions
    • Modules
    • File operations
    • Exception Handling
    • List Comprehension
    • Lambda Functions
    • Generators
    • Iterators
    • Concepts of Numpy
    • ndArrays
    • Basic & Matrix Operations
    • Increment and Decrement Operations
    • Indexing, Slicing
    • Iterating Array
    • Conditional Operations
    • Shape & Array Manipulation
    • Universal Functions
    • General Concepts and Broadcasting
    • Loading and saving files
    • Reading and Writing Array Data on Files
    • Assignments & Problem Statements
    • What is Pandas
    • Pandas Series
    • Pandas DataFrame
    • DataFrame Indexing and Loading
    • Querying a DataFrame
    • Indexing Dataframes
    • Missing Values
    • Assignments & Problem Statements
    • Working with Databases
    • How to create a Database instance on Cloud
    • CREATE Table Statement
    • SELECT Statement
    • COUNT, DISTINCT, LIMIT
    • INSERT, UPDATE and DELETE Statements
    • Information and Data Models
    • Types of Relationships
    • Sub-Queries and Nested Selects
    • Introduction to Machine Learning
    • Understanding Supervised Learning.
    • Linear Regression Theory
    • Supervised Learning Regression
    • Linear Regression
    • Multiple Linear Regression
    • Bias-Variance Trade-Off
    • Logistic Regression
    • K-Nearest Neighbors (KNN)
    • Simple Vector Machine (SVM)
    • Decision Trees
    • Bagging
    • Boosting, AdaBoost & XGBoost
    • Naïve Bayes Classifier
    • K-Means Clustering
    • Hierarchical Clustering
    • Dimensionality Reduction
    • Linear Discriminant Analysis
    • Time Series Modelling
    • Principal Component Analysis (PCA)
    • Reinforcement Learning
    • Model Comparisons
    • Analysis Considerations
    • Clustering Animals
    • Customer Segmentation
    • Optimal Number of Clusters
    • Cluster Based Incentivization
    • Image Segmentation
    • What is Neural Networks
    • Gradient Descent
    • Perceptron & Neural Networks
    • Batch Normalization
    • Activation and Loss functions
    • Hyper parameter tuning
    • Deep Neural Networks
    • Tensor Flow & Keras for Neural Networks & Deep Learning
    • Understand Neural Networks in Detail
    • PyTorch Tensors
    • PyTorch Autograd
    • Illustrate Multi-Layer Perceptron
    • Backpropagation – Learning Algorithm
    • Understand Backpropagation – Using Neural Network Example
    • MLP Digit-Classifier using TensorFlow
    • Building a multi-layered perceptron for classification
    • Overview of Neural Network
    • Bias-Variance Trade-off
    • TensorFlow & Keras
    • Multi-layered Perception(MLP)
    • Feed-forward & Backpropagation
    • Activation Functions
    • Optimization techniques
    • Dropout
    • Gradient Descent & Stochastic Gradient Descent
    • Kernels
    • Padding & Strides
    • Convolutional Layer
    • Max-Pooling
    • CNN Architectures – VGGNet, AlexNet, Inception Network
    • Assignments & Problem Statements
    • Project on CNN
    • RNN & LSTM:
    • Recurrent
    • Recurrent Neural Network
    • Backpropagation in RNN.
    • Types of RNN
    • Architecture of RNN
    • LSTM (Long short term memory)
    • Architecture of LSTM
    • Link with Linear Regression
    • Recurrent Neural Network
    • Backpropagation in RNN.
    • Why Sequence Model
    • RNN Model
    • Backpropagation through time
    • Different Type of RNNs
    • GRU
    • LSTM
    • Bidirectional LSTM
    • Deep RNN
    • Word Embedding
    • Understanding NLP
    • Stop Words, Tokenization
    • Stemming and lemmatization
    • Bag of Words Model
    • Word Vectorizer
    • POS Tagging
    • ANN Intuition
    • Plan of Attack
    • Studying the Neuron
    • The Activation Function
    • Working of Neural Networks

Course Curriculum

Learn what you'll get after successful enrollment in our course for Artificial Intelligence!

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Experience Our Artificial Intelligence Certification Training Journey!

  • Introduce yourself to the concepts, principles and working knowledge of Artificial Intelligence
  • Understand the real world scenarios with real-time job oriented projects and case studies
  • Learn from World Class Trainers who are one amongst the top rated working IT Professionals
  • Clear your certifications while we make you ready for the huge job market present out there

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