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Artificial Intelligence Masters Program Training Course

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Rated #1 Recognized as the No.1 Institute for Artificial Intelligence Masters Program Training Course

Enhance your career potential with our Artificial Intelligence Masters Program Training Course. Our extensive training, guided by industry experts, offers a deep dive into AI technologies, equipping you with the skills to design and implement intelligent solutions that foster business innovation and growth.

The Artificial Intelligence Masters Program Course covers essential tools and techniques like machine learning, deep learning, natural language processing (NLP), and data science, preparing you to tackle real-world AI applications. With personalized guidance, artificial intelligence online training, and job placement support, you’ll be well-positioned to succeed in the ever-expanding AI sector.

Our curriculum follows industry best practices, ensuring you’re job-ready from day one.
Enroll our AI Masters Program Certification Training to unlock career growth opportunities.
Earn your AI Master program Training with placement and elevate your professional credentials.
Advance your expertise with our AI Masters program, supported by over 400 recruitment partners.
Hands-on projects and making this program the perfect foundation for advancing your career in AI.

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Download Syllabus

Course 1

Artificial Intelligence
Course 2

Data Science with Python
Course 3

Machine Learning
Course 4

Deep Learning with TensorFlow
View 5 more courses

Course 5

Advanced Deep Learning

Course 6

Natural Language Processing

Course 7

AI Capstone Project

Hands-on Project

(Machine Learning Models, NLP Applications, Predictive Analytics)

Add On

(Recorded Video, Group Discussion, 1-on-1 Sessions)

Job Preparation

(Aptitude, Resume Preparation, Mock Interview)
Master’s Certificate

*Distinct certificates awarded for each course.

28-Apr-2025

Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

30-Apr-2025

Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

03-May-2025

Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session

04-May-2025

Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

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Outline of Artificial Intelligence Masters Program

We train students for interviews and Offer Placements in top corporate companies.
Suitable for Graduates and Experienced Candidates from any Technical Background
You will only gain knowledge of Artifical Intelligence and Advance tools, but also gain exposure to Industry best practices, Aptitude & SoftSkills
Experienced Trainers and sophiticated Lab Facility
IBM Certification Guidance Support with Exam Dumps
For Corporate, we act as one stop recruiting partner. We provide right skilled candidates who are productive right from day one
Guidance for Resume & Interviews Preparation Support
Learning Concepts: AI- Artifical Intelligence Concepts, Data Science with Python, Machine Learning, Deep Learning with Keras and TensorFlow, Advanced Deep Learning and Computer Vision etc
START YOUR CAREER WITH ARTIFICAL INTELLIGENCE COURSE THAT GETS YOU A JOB OF UPTO 5 LACS IN JUST 60 DAYS!

Classroom Batch Training
One To One Training
Online Training
Customized Training
Enroll Now

About Artificial Intelligence Masters Program Training Course

We would do whatever it takes to make this a definitive Artificial Intelligence Masters Program course. This would be your unique destination to learn Artificial Intelligence Masters Program.

Learning Artificial Intelligence Masters Program can help open up many opportunities for your career. It is a great skill-set to have as many roles in the job market requires proficiency in AI Masters. Mastering Artificial Intelligence Masters Program can help you get started with your career in IT Companies like Paypal, Capgemini, Accenture, Mphasis, CTS and MindLabs, etc, are all hiring Intelligence Designer.

This course will not only cover the core issues but will also cover many more advanced topics. This course is going to be one of the most comprehensive courses on ACTE. AI Concepts, Data Science with Python, Machine Learning, Deep Learning with Keras and TensorFlow, Advanced Deep Learning and Computer Vision; THERE IS NO PROBLEM. Everything is covered.

Best Job Oriented Topics Covered

Concepts of AI

Natural Language Processing (NLP)

Datascience concepts
Data Science with Python

Deep Learning with Keras and TensorFlow

AI capstone project
Machine Learning Concepts

Advanced Deep Learning and Computer Vision

Python Packages

Is Artificial Intelligence Masters Program a good career choice?

Artificial Intelligence has opportunities with high pay, a growing number of intriguing sub-fields, and the ability to work with life-changing technology daily. Specific jobs that use AI are software engineers, data analysts, and roboticists.

What is the scope of Artificial Intelligence Masters Program?

Artificial intelligence is impacting the long run of nearly every business. It acted because the driver of rising technologies like huge information, robotics, and IoT, and it'll continue as a technological originator for the predictable future.

What background knowledge is necessary?

AI technology permits the capability of understanding, reasoning, planning, communication, and perception – to be undertaken by software systems more and more effectively, expeditiously, and at low prices. Applications of AIpowered laptop vision are going to be significantly vital within the transport sector.

Will ACTE Help Me With Placements After My Artificial Intelligence Masters Program Course Completion?

We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for developer. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.

How Does AI works?

AI works by combining giant amounts of knowledge with quick, repetitive processes and intelligent algorithms, permitting the software package to be told mechanically from patterns or options within the knowledge.

What are the prerequisites for learning Artificial Intelligence Masters Program?

Concepts of AI/li>
Data Science with Python
Machine Learning Concepts
Natural Language Processing (NLP)
Deep Learning with Keras and TensorFlow
Advanced Deep Learning and Computer Vision.

Does Artificial Intelligence Masters Program require coding?

Artificial Intelligence certified Intelligence Designer should know at least know the basics of programming languages like Python etc. Knowledge of various technology like AI Algorithms, Machine Learning, etc.

Will I Be Given Sufficient Practical Training In Artificial Intelligence Masters Program?

Our courseware is designed to give a hands-on approach to the students in Artificial Intelligence Masters Program. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.

Who can learn Artificial Intelligence Masters Program?

Anyone from computer or Engineering background holder can start to learn the AI Master Program. Artificial Intelligence necessity for information of a programming (computer) language like Python then etc. Being a Freshers in AI is not about familiarity; it's about an intuitive and deep understanding all the technologies related to AI practices and paradigms.

How long would it take to master in Artificial Intelligence Masters Program?

Three-Four months is long enough to learn a considerable amount of Artificial Intelligence Masters Program. If you are already able to fluently program in another language, then 2 months would be a generous amount of time to learn enough Artificial Intelligence Masters Program to meaningfully contribute in a professional capacity.

Top reasons to consider a career in Artificial Intelligence Masters Program?

The Demand for Artificial Intelligence Masters Program is high.
The average salary of Freshers Masters developers in India is around 8 LPA.
Creative Flexibility.
You know about multiple aspects of development.
Better Productivity.

Key Features

ACTE offers rtificial Intelligence Masters Program Training in more than 27+ branches with expert trainers. Here are the key features,

160 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS .

Artificial Intelligence Master Program Course Content

Artificial Intelligence

Syllabus of Artificial Intelligence

Module 1: Introduction to Data Science

What is Data Science?
What is Machine Learning?
What is Deep Learning?
What is AI?
Data Analytics & it’s types

Module 2: Introduction to Python

What is Python?
Why Python?
Installing 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 & Labels

Module 4: Python Packages

Pandas
Numpy
Sci-kit Learn
Mat-plot library

Module 5: Importing Data

Reading CSV files
Saving in Python data
Loading Python data objects
Writing data to csv file

Module 6: Manipulating Data

Selecting rows/observations
Rounding Number
Selecting columns/fields
Merging data
Data aggregation
Data munging techniques

Module 7: Statistics Basics

Central Tendency
Probability Basics
Standard Deviation
Bias variance Trade off
Distance metrics
Outlier analysis
Missing Value treatment
Correlation

Module 8: Error Metrics

Classification
Regression

Module 9: Machine Learning

Supervised Learning
Linear Regression
Logistic regression

Module 10: Unsupervised Learning

K-Means
K-Means ++
Hierarchical Clustering

Module 11: SVM

Support Vectors
Hyperplanes
2-D Case
Linear Hyperplane

Module 12: SVM Kernal

Linear
Radial
polynomial

Module 13: Other Machine Learning algorithms

K – Nearest Neighbour
Naïve Bayes Classifier
Decision Tree – CART
Decision Tree – C50
Random Forest

Module 14: AI

Perceptron
Multi-Layer perceptron
Markov Decision Process
Logical Agent & First Order Logic
AL Applications

Module 15: Deep Learning Algorithms

CNN – Convolutional Neural Network
RNN – Recurrent Neural Network
ANN – Artificial Neural Network

Module 16: Introduction to NLP

Text Pre-processing
Noise Removal
Lexicon Normalization
Lemmatization
Stemming
Object Standardization

Module 17: Text to Features

Syntactical Parsing
Dependency Grammar
Part of Speech Tagging
Entity Parsing
Named Entity Recognition
Topic Modelling
N-Grams
TF – IDF
Frequency / Density Features
Word Embedding’s

Module 18: Tasks of NLP

Text Classification
Text Matching
Levenshtein Distance
Phonetic Matching
Flexible String Matching

Data Science with Python

Syllabus of Data Science with Python Course

Module 1: Introduction to Data Science

What is Data Science?
What is Machine Learning?
What is Deep Learning?
What is AI?
Data Analytics & it’s types

Module 2: Introduction to Python

What is Python?
Why Python?
Installing 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 & Labels

Module 4: Python Packages

Pandas
Numpy
Sci-kit Learn
Mat-plot library

Module 5: Importing data

Reading CSV files
Saving in Python data
Loading Python data objects
Writing data to csv file

Module 6: Manipulating Data

Selecting rows/observations
Rounding Number
Selecting columns/fields
Merging data
Data aggregation
Data munging techniques

Module 7: Statistics Basics

Central Tendency
Mean
Median
Mode
Skewness
Normal Distribution
Probability Basics
What does mean by probability?
Types of Probability
ODDS Ratio?
Standard Deviation
Data deviation & distribution
Variance
Bias variance Trade off
Underfitting
Overfitting
Distance metrics
Euclidean Distance
Manhattan Distance
Outlier analysis
What is an Outlier?
Inter Quartile Range
Box & whisker plot
Upper Whisker
Lower Whisker
catter plot
Cook’s Distance
Missing Value treatments
What is a NA?
Central Imputation
KNN imputation
Dummification
Correlation
Pearson correlation
Positive & Negative correlation
Error Metrics
Classification
Confusion Matrix
Precision
Recall
Specificity
F1 Score
Regression
MSE
RMSE
MAPE

Module 8: Machine Learning

Module 9: Supervised Learning

Linear Regression
Linear Equation
Slope<
Intercept
R square value
Logistic regression
ODDS ratio
Probability of success
Probability of failure
ROC curve
Bias Variance Tradeoff

Module 10: Unsupervised Learning

K-Means
K-Means ++
Hierarchical Clustering

Module 11: Other Machine Learning algorithms

K – Nearest Neighbour
Naïve Bayes Classifier
Decision Tree – CART
Decision Tree – C50
Random Forest

Machine Learning

Syllabus of Machine Learning Course

Module 1: Introduction to Data Analytics

Business Analytics, Data, Information
Understanding Business Analytics and R
Compare R with other software in analytics
Install R
Perform basic operations in R using command line
Learn the use of IDE R Studio
Use the ‘R help’ feature in R

Module 2: Introduction to R programming

Variables in R
Scalars
Vectors
Matrices
List
Data frames
Using c, Cbind, Rbind, attach and detach functions in R
Factors

Module 3: Data Manipulation in R

Data sorting
Find and remove duplicates record
Cleaning data
Recoding data
Merging data
Slicing of Data
Merging Data
Apply functions

Module 4: Data Import techniques in R

Reading Data
Writing Data
Basic SQL queries in R
Web Scraping

Module 5: Exploratory data Analysis

Box plot
Histogram
Pareto charts
Pie graph
Line chart
Scatterplot
Developing Graphs

Module 6: Basics of Statistics & Linear & Logistic Regression

Basics of Statistics
Inferencial statistics
Probability
Hypothesis
Standard deviation
Outliers
Correlation
Linear & Logistic Regression

Module 7: Data Mining: Clustering techniques, Regression & Classification

Introduction to Data Mining
Understanding Machine Learning
Supervised and Unsupervised Machine Learning Algorithms
K- means clustering

Module 8: Anova & Sentiment Analysis

Anova
Sentiment Analysis

Module 9: Data Mining: Decision Trees and Random Forest

Decision Tree
Concepts of Random Forest
Working of Random Forest
Features of Random Forest

Module 10: Project work

Deep Learning with TensorFlow

Syllabus of Deep Learning Course with TensorFlow Training Course

Module 1: Essential Programming

Introduction to Deep Learning
Introduction to Numpy
Introduction to Tensorflow and Keras

Module 2: Essential basics of Linear Algebra

Solution of Equations, row and column Interpretation
Vector Space Properties
Partial Derivative of Polynomial and Two conditions for Local Minima
Physical Interpretation of gradient (Direction of Maximum Change)
Matrix Vector Multiplication
EVD and interpretation of Eighen Vectors
Linear Independence and Rank of Matrix
Orthonormal Matrices, Projection Matrices, Vandemonde Matrix, Markov Matrix, Symmetric, Block Diagonal

Module 3: Selected topics of Machine Learning

Intuition behind Linear Regression, classification
Grid Search
Gradient Descent
Training Pipeline
Metrics ROC Curve, Precision Recall Curve
Calculating Entropy

Module 4: Basics of Neural Network

Evolution of Perceptrons, Hebbs Principle, Cat Experiment
Single layer NN
Tensorflow Code
Multilayer NN
Back propagation, Dynamic Programming
Mathematical Take on NN
Function Approximator
Link with Linear Regression
Dropout and Activation
Optimizers and Loss Functions

Module 5: Introduction to Convolutional Neural Network

1D and 2D Convolution
Why CNN for Images and speech?
Convolution Layer
Coding Convolution Layer
Learning Sharpening using single convolution Layer in Tensor-Flow

Module 6: Different Layers in CNN pipeline

Convolution
Pooling
Activation
Dropout
Batch Normalization
Object Classification
Creating Batch in Tensorflow and Normalize
Training MNIST and CIFAR datasets
Understanding a pre-trained Inception Architecture
Input Augmentation Techniques for Images

Module 7: Transfer Learning

Finetuning last layers of CNN Model
Selecting appropriate Loss
Adding a new class in the last Layer
Making a model Fully Convolutional for Deployment
Finetune Imagenet for Cats vs Dog Classification.

Module 8: Object Detection and Localization

Different types of problem in Objects
Difficulties in Object Detection and Localization
Fast RCNN
Faster RCNN
YOLO v1-v3
SSD
MobileNet

Module 9: Autoencoders

Image Compression Simple Autoencoder
Denoising Autoencoder
Variational Autoencoder and Reparematrization Trick
Robust Word Embedding using Variational Autoencoder

Module 10: Time Series Modelling

Evolution of Recurrent Structures
LSTM, RNN, GRU, Bi-RNN, Time-Dense
Learning a Sine Wave using RNN in Tensorflow
Creating Autocomplete for Harry Potter in Tensorflow

Module 11: GANs

Generative vs Discrimative Models
Theory of GAN
Simple Distribution Generator in Tensorflow using MCMC (Markov Chain Monte Carlo)
DCGAN,WGANs for Images
InfoGANs, CycleGANs and Progressive GANs
Creating a GAN for generating Manga Art

Module 12: Model Free Approaches in Reinforcement Learning

Model Free Prediction
Monte Carlo Prediction and TD Learning
Model Free Control with REINFORCE and SARSA Learning
Assignment : Implementation of REINFORCE and SARSA Learning in Gridworld
Off policy vs On Policy Learning
Importance Sampling for Off Policy Learning
Q Learning

Module 13: Behavioral Cloning and Deep Q Learning

Understanding Deep Learning as Function Approximator
Theory of Behavioral Cloning and Deep Q Learning
Revisiting Point Collector Example in Unity and
Assignment : Training Cartpole Example via Deep Q Learning

Module 14: Deep Learning in Action

Face Detection using Yolo-v3
Building Autocomplete Feature using RNNs
Real-time Depth Prediction and Pose Estimation
How is Deep Learning used in Autonomous Driver Assistant systems
Tips and Tricks for scaling and easy Deployment of Deep Learning Models

Advanced Deep Learning

Syllabus of Advanced Deep Learning Course

Module 1: Introduction to Data Science

What is Data Science?
What is Machine Learning?
What is Deep Learning?
What is AI?
Data Analytics & it’s types

Module 2: Introduction to Python

What is Python?
Why Python?
Installing 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 & Labels

Module 4: Python Packages

Pandas
Numpy
Sci-kit Learn
Mat-plot library

Module 5: Importing Data

Reading CSV files
Saving in Python data
Loading Python data objects
Writing data to csv file

Module 6: Manipulating Data

Selecting rows/observations
Rounding Number
Selecting columns/fields
Merging data
Data aggregation
Data munging techniques

Module 7: Statistics Basics

Central Tendency
Mean
Median
Mode
Skewness
Normal Distribution
Probability Basics
What does mean by probability?
Types of Probability
ODDS Ratio?
Standard Deviation
Data deviation & distribution
Variance
Bias variance Trade off
Underfitting
Overfitting
Distance metrics
Euclidean Distance
Manhattan Distance
Outlier analysis
What is an Outlier?
Inter Quartile Range
Box & whisker plot
Upper Whisker
Lower Whisker
Scatter plot
Cook’s Distance
Missing Value treatment
What is a NA?
Central Imputation
KNN imputation
Dummification
Correlation
Pearson correlation
Positive & Negative correlation

Module 8: Error Metrics

Classification
Confusion Matrix
Precision
Recall
Specificity
F1 Score
Regression
MSE
RMSE
MAPE

Module 9: Machine Learning

Supervised Learning
Linear Regression
Linear Equation
Slope
Intercept
R square value
Logistic regression
ODDS ratio
Probability of success
Probability of failure Bias Variance Tradeoff
ROC curve
Bias Variance Tradeoff
Unsupervised Learning
K-Means
K-Means ++
Hierarchical Clustering
SVM
Support Vectors
Hyperplanes
2-D Case
Linear Hyperplane
SVM Kernal
Linear
Radial
Polynomial
Other Machine Learning algorithms
K – Nearest Neighbour
Naïve Bayes Classifier
Decision Tree – CART
Decision Tree – C50
Random Fores

Module 10: Artificial Intelligence

AI Introduction
Perceptron
Multi-Layer perceptron
Markov Decision Process
Logical Agent & First Order Logic
AL Applications

Module 11: Deep Learning Algorithms

CNN – Convolutional Neural Network
RNN – Recurrent Neural Network
ANN – Artificial Neural Network
Introduction to NLP
Text Pre-processing
Noise Removal
Lexicon Normalization
Lemmatization
Stemming
Object Standardization
Text to Features (Feature Engineering)
Syntactical Parsing
Dependency Grammar
Part of Speech Tagging
Entity Parsing
Named Entity Recognition
Topic Modelling
N-Grams
TF – IDF
Frequency / Density Features
Word Embedding’s
Tasks of NLP
Text Classification
Text Matching
Levenshtein Distance
Phonetic Matching
Flexible String Matching

Module 12: Design Effective Reports

Enhance report design
Add report objects to enhance design
Format data and report objects
Add a background image to a report
Add row numbers to a report

Module 13: Customize Reports with Conditional Formatting

Create multi-lingual reports
Highlight exceptional data
Show and hide data
Conditionally render objects in reports

Module 14: Analysis Studio

Analysis Studio Fundamentals
Nest Data in Crosstabs in Analysis Studio
Create Analysis with Multiple filter
Reusable analysis
Build Advanced Crosstabs in Analysis Studio
Focus with Filters in Analysis Studio
Creating reports from cubes
Drill down and drill up

Module 15: Event Studio

Introduction to Event Studio
Create an agent
Add tasks to an agent
Run an agent through its lifecycle
Schedule an agent

Module 16: Business Insight

Introdcution to Dashboards
Create Dashboard
Types of Filter-Value, Slider and advanced filter
Overview of RSS Feed and web Page
Content Pane
Create Widgets
Sort, Filter and Calculate data
Hands on

Module 17: Business Insight Advanced

Overview of Business Intelligence Advance level
Create Different types of Reports
Reporting Styles and filters
Create dashboard objects
Summarize data and Create Calculations
Dispatcher and Services

Module 18: Dispatcher in detail

All Services
Properties of Services

Natural Language Processing

Syllabus of Natural Language Processing (NLP) Training Course

Module 1: Introduction to NLP and Deep Learning

Overview of Natural Language Processing
Machine learning methods
Cutting-edge deep learning methods

Module 2: Neural models for machine translation and conversation

Introduction to Statistical Machine Translation
Introduction to neural models
Introduction to neural models for translation and conversation

Module 3: Deep Semantic Similarity Models

Introduction to Deep Semantic Similarity Model (DSSM) and its applications.

Module 4: Natural Language Understanding

Introduction to methods applied in Natural Language Understanding
Continuous word representations method
Neural knowledge base embedding method

Module 5: Deep reinforcement learning in NLP

Introduction to deep reinforcement learning techniques applied in NLP

Module 6: Vision-Language Multimodal Intelligence

Neural models applied in Image captioning
Neural models applied in visual question answering

AI Capstone Project

Syllabus of AI Capstone Project Course

Module 1: Exploratory Data Analysis

Exploratory Data Analysis

Module 2: Model Building and fitting

Model Building and fitting

Module 3: Unsupervised learning

Unsupervised learning

Module 4: Representing results

Representing results

Show Less

Need customized curriculum?

Hands-on Live Projects in Aritificial Intelligence

Project 1

House Price Predicting System

This project have the dataset contain the price of a house in different areas and get the data from varies resources.

Project 2

Customer Recommendation Application

It will browsing history of the customer for your data and the platform in enhancing its income tremendously thanks to customer.

Project 3

Facial Emotion Recognition and Detection

It can detect the human emotions in real-time, including happy, sad, angry, afraid, surprise, disgust, and neutral.

Project 4

Voice-based Virtual Assistant System

It is a handy tool for simplifying everyday tasks like to search for items on the Web, to shop for products etc.

This is How ACTE Students Prepare for Better Jobs

Internship and Practical Experience

Gain invaluable hands-on experience through our internship program, where theoretical knowledge meets practical application. Elevate your skills, expand your network, and pave the way for a successful career journey.

Hands On Projects

Experienced in leading hands-on projects, applying technical skills to drive successful outcomes. Proficient in project management and collaboration to ensure effective execution and delivery.

Resume Preparation

Expertise in developing standout resumes that effectively showcase your skills, experience, and achievements, maximizing your chances of securing interviews and advancing your career goals.

Apptitude and Technical skills

Develop your aptitude and technical prowess with our comprehensive training programs. Master essential skills, stay ahead of industry trends, and unlock new opportunities for professional growth and success.

Mock Interview

Hone your interview skills with our realistic mock interview sessions tailored to your desired role. Gain confidence, refine your responses, and secure your dream job.

Group Discussion

Engage in dynamic group discussions to enhance communication, teamwork, and critical thinking skills. Cultivate confidence and articulate your ideas effectively in a collaborative setting.

Until You Get a Job in Top MNC

Persevere until you secure a position in a top-tier MNC, where your expertise is valued, and your career aspirations are fulfilled. Stay focused, determined, and relentless in your pursuit of success.

Employee Referal Program

Empower your network by referring talented individuals to join our team, and reap rewards through our Employee Referral Program. Together, let's build a stronger workforce and create opportunities for growth and success.

Our Top Hiring Partner for Placements

ACTE offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.

We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
After completion of 70% rtificial Intelligence Masters Program training course content, we will arrange the interview calls to students & prepare them to F2F interaction
rtificial Intelligence Masters Program Trainers assist students in developing their resume matching the current industry needs
We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

Be a Certified Expert in Artificial Intelligence Masters Program

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees.

Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

Get Certified

About Experienced Artifical Intelligence Master Programming Trainers

Our Artificial Intelligence Master Program Course : Trainers are certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
As all Trainers are AI domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best Artificial Intelligence training to the students.
We have received various prestigious awards for Artificial Intelligence Training recognized IT organizations.

Artificial Intelligence Masters Program Training Course FAQs

Looking for better Discount Price?

Call now: +91-7669 100 251 and know the exciting offers available for you!

Does ACTE provide placement?

ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
More than 3500+ students placed in last year in India & Globally
ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
85% percent placement record
Our Placement Cell support you till you get placed in better MNC
Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions

Is ACTE certification good?

ACTE

Certificate

Certification is Accredited by all major Global Companies
ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS

Work On Live Projects?

The entire Artificial Intelligence Masters Program Training Course in training has been built around Real Time Implementation
You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
GitHub repository and Showcase to Recruiters in Interviews & Get Placed

Who are the Trainers?

All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.

What if I miss one (or) more class?

No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.

What are the modes of training offered for this Artificial Intelligence Masters Program Training Course?

We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Artificial Intelligence Masters Program Training Course At ACTE?

Artificial Intelligence Masters Program Training Course Course in ACTE is designed & conducted by Artificial Intelligence Masters Program Training Course experts with 10+ years of experience in the Artificial Intelligence Masters Program domain
Only institution in India with the right blend of theory & practical sessions
In-depth Course coverage for 60+ Hours
More than 50,000+ students trust ACTE
Affordable fees keeping students and IT working professionals in mind
Course timings designed to suit working professionals and students
Interview tips and training
Resume building support
Real-time projects and case studies

Can I Access the Course Material in Online?

Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.

What certification will I receive after course completion?

You will receive ACTE globally recognized course completion certification Along with project experience, job support, and lifetime resources.

How Old Is ACTE?

We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.

What Will Be The Size Of A Artificial Intelligence Masters Program Training Course Batch At ACTE?

We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Artificial Intelligence Masters Program Training Course batch to 5 or 6 members

Will I Be Given Sufficient Practical Training In Artificial Intelligence Masters Program Training Course?

Our courseware is designed to give a hands-on approach to the students in Artificial Intelligence Masters Program Training Course. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.

How Do I Enroll For The Artificial Intelligence Masters Program Training Course At ACTE?

You can contact our support number at +91-7669 100 251 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India

Corporate Training

If you want to give the Trending technology experience to your esteemed employees, we are here to help you!

Group Discount

If you have Three or more people in your training we will be delighted to offer you a group discount.

3 to 4 Peoples

10%

5 to 9 Peoples

15%

10+ Peoples

20%

Request for Class Room & Online Training Quotation

Class Room
Online

Other Category Placements

Non-IT to IT (Career Transition) 2371+
Diploma Candidates3001+
Non-Engineering Students (Arts & Science)3419+
Engineering Students3571+
CTC Greater than 5 LPA4542+
Academic Percentage Less than 60%5583+
Career Break / Gap Students2588+

Top Placement Record

True Reviews & Placed Students

Pooja

Make an Impression with your Digital Marketing in Just 2 Minutes!

Pooja cracked a career at

6 LPA

Career Break

Digital Marketing

Dinesh

No more dull edges, Watch OUT? And Move Faster and Reach Farther

Dinesh cracked a career at

4 LPA

Non-IT

java Developer

Bargavi

Transform your life through education, Hear It from Our Alumni

Bargavi cracked a career at

7 LPA

Fresher

Software Developer

Shiva Kumar

Want to Make a Career change in Genpact, Watch What Our Freshers Say

Shiva Kumar cracked a career at

5 LPA

Manual Testing

Automation Testing

Harshatha

Wish to nurture your Career in Software testing? Watch Out the Learner’s Journey From ACTE

Harshatha cracked a career at

6 LPA

Fresher

Software testing

Riya

Want To Move up in your career with Java J2EE, Here from ACTE Learners outcome survey

Riya cracked a career at

4 LPA

Fresher

Java Developer

Job Opportunities in Artificial Intelligence

More Than 35% Prefer Artificial Intelligence for Automating Tasks. Artificial Intelligence is One of the Most Popular and In-Demand Technologies in the Automated World.