Close Icon

Our Training Process

training process
training process

Key Highlights of the Program

  • Personalized Career Coach
    Personalized Career Coach
  • 80% Practical Training
    80% Practical Training
  • 2 Global Certifications
    2 Global Certifications
  • Guaranteed Internship
    Guaranteed Internship
  • Study App/Material
    Study App/Material
  • Instant Doubt Solving
    Instant Doubt Solving
  • 100% Job Assurance
    100% Job Assurance
  • 40+ Case Studies & Projects
    40+ Case Studies & Projects
  • No Cost EMI Option
    No Cost EMI Option
  • Job or Refund Program
    Job or Refund Program
Freshers Enrolled
7000+

Freshers Enrolled

Personalized Coaching
1:1

Personalized Coaching

Tie Up Companies
250+

Tie Up Companies

Avg. Salary Drawn
3-15 lakhs P.A

Avg. Salary Drawn

Data Science with AI & AWS Curriculum

Diving into the World of Data
Weeks 2 Weeks
  • Data analytics Life Cycle
  • How to see Data?
  • Descriptive Statistics
  • Probability
  • Inferential Statistics
  • Algebra and Derivative
  • What is Computer Program ?
  • Procedure to find Problem Solution
  • Algorithms
  • Flowcharts
Excel & Advance Excel
Self Learning
  • Introduction To Excel
  • Creating a new Workbook & managing workbook
  • Range Selection
  • Sharing Workbook
  • Filling Data
  • Formula and Function
  • Formula Referencing
  • Font, Text, Number, Date, Currency Formating
  • Printing and Page Setups
  • Advance Excel
  • Vlookup Hlookup
  • What if analysis
  • Pivot Table
  • Data Visualization
  • Regression Analysis
Tableau Shelf and Card
Self Learning
  • Introduction to Tableau
  • Tableau Shelf & Cards
  • Connecting to & Preparing Data
  • Organizing & Simplifying Data
  • Fields & Charts
  • Analytics
  • Tableau Dashboards
SQL
Weeks 2 Weeks Projects 1 Projects
  • Introduction to SQL
  • Data Definition Language(DDL)
  • Data Manipulation Language(DML)
  • Data Query Language(DQL)
  • Sub query Correlated subquery Joins
  • View & Indexes
Python
Weeks 8 Weeks Projects 2 Projects
  • Introduction To Python
  • Setup for Python & Anaconda
  • Data Type, Variable & Operators
  • Conditional Statements
  • Iterative Statements
  • Functions
  • Modules
  • File Handling
  • OOP
  • Exception Handling
  • Regex, Web scrapping using Beautiful Soup & Selenium
  • DataBase connectivity
  • Flask
Credit card fraud detection

Web scrapping & Data analytics using python

Analytics with Python
Weeks 1.5 Weeks Projects 2 Projects
  • Pandas
  • Numpy
  • Seaborn
  • Matplotlib
Machine Learning
Weeks 6 Weeks Projects 3 Projects
  • Introduction to ML
  • Regression - Linear & Polynomial
  • Classification - Logistic Regression
  • Decision Tree
  • Random Forest
  • Support Vector Machine
  • Clustering - KMeans and Hierarchical
  • Principal Component Analysis
  • Association Rules
  • Network analysis
R Programming
Weeks 3 Weeks Projects 1 Projects
  • Introduction to R Programming
  • Advance R Programming
  • Data IO
  • Data Analysis using R Programming
  • Data Manipulation using R Programming/ Exploratory Data Analysis
  • Data Visualization using R Programming
Machine Learning with R
Self Learning
  • Machine Learning with R Video
Big Data
Weeks 3 Weeks Projects 3 Projects
  • Introduction to Big Data
  • Hadoop Framework Hadoop Commands
  • Data loading using SQOOP and Flume
  • Data Analysis using Pig and Hive
  • Machine Learning using Apache Spark
Deep Learning
Weeks 4 Weeks Projects 2 Projects
  • Machine Learning Primer (Linear and Logistic Regression)
  • What is Deep Learning
  • What is Artificial Intelligence
  • Applications of AI
  • Machine Learning vs Deep Learning
  • Introduction to Google colab
  • Deep Learning Frameworks
  • Tensorflow low level APIs
  • Human Brain and Neuron
  • Rosenblatt's Perceptron
  • Linear vs Non-Linear Problem (Tensorflow Playground)
  • Artificial Neuron (Integration and Activation Functions)
  • Artificial Neural Network
  • Introduction to Gradient Descent
  • Loss & Cost Function
  • Forward and Backward Propagation
  • Local vs Global Minima
  • Stochastic Gradient Descent
  • Mini-Batch Gradient Descent
  • Momentum & Nestrov Momentum
  • Adagrad, Adadelta, RMSProp, Adam
  • Linear, Sigmoid, Tanh Activation
  • Neural Network for Regression
  • Neural Network for Binary Classificarion
  • Vanishing Gradient Problem
  • RELU and Leaky RELU Activation
  • Softmax Activation
  • Neural Network for Multi-class Classification
  • L1 and L2 Regularization
  • Dropout Layer
  • Callbacks and Early Stopping
  • Batch Normalization
Natural Language Processing
Weeks 6 Weeks Projects 2 Projects
  • Text Mining vs Natural Language Processing
  • Tokenization
  • Stopwords Removal
  • Stemming and Lemmatization
  • Parts Of Speech Tagging
  • Named Entity Recognition
  • Text Visualization
  • Bag-of-Words (CountVectorizer)
  • TF-IDF Vectorizer
  • Text classification using Machine Learning
  • Keras Tokenizer
  • Sequence Padding
  • Embedding Layer
  • Flatten Layer
  • Text classification using NN
  • Glove Embedding
  • What is Sentiment Analysis
  • Challages in Sentiment Analysis
  • Extracting Sentiments from Web
  • Handling Emoticons
  • Sentiment Analysis using ANN
  • Sequential Data
  • Recurrent Neural Network
  • Multi-layer and Bi-directional RNN
  • Architectures of RNN
  • Vanishing Gradient Problem in RNN
  • Long Short Term Memory
  • Multi-layer and Bi-directional LSTM
  • Gated Recurrent Unit
  • Multi-layer and Bi-directional GRU
  • Sequence To Sequence Model
  • Attention Mechanism
  • Transformer
  • BERT
  • Document Summarization using BERTSUM
  • GPT
  • XLNET
  • What is RASA
  • RASA Installation
  • RASA Initialization
  • RASA Configuration and File System
  • Intents, Entity,Response and Story
  • Actions
Computer Vision
Weeks 5 Weeks Projects 2 Projects
  • Introduction to computer vision
  • Computer vision Application
  • Digital Image Processing
  • Computer Vision vs DIP
  • what is an Image ?
  • How computer undestand Images.
  • Computer Vision Process cycle
  • Installation guide OpenCV, imutils
  • Digital Image processing using OpenCV
  • OCR using OpenCV & Pytesseract
  • Traditional Object Detection using Haar Cascade
  • Introduction To CNN
  • Convolution and Pooling
  • Implementation
  • Image Augmentation
  • Transfer Learning VGG16, MobileNet
  • Pricipal of Object Detection RCNN,YOLO
  • Gender, Age, Emotion recognition
  • Face Recognition using VGGFace
  • Computer Vision World Alternative Frameworks Pytorch,MXnet,Theano Google API,ClarifAI Amazon
  • Mediapipe
Time Series
Weeks 3 Weeks Projects 1 Projects
  • Intorduction to Time series
  • Understanding Time Series Data
  • Regularization
  • Visualizing and Understanding Time SeriesComponents
  • Autocovariance
  • ACF and PACF
  • Autoregressive models: AR, MA, ARMA, ARIMA
  • Time series forecasting using RNN & LSTM
Recommander System
Weeks 2 Weeks Projects 1 Projects
  • Introduction to Recommender system
  • Collaborative Filtering
  • Matrix Factorization
AI using AWS
Weeks 3 Weeks Projects 1 Projects
  • What is AI ?
  • Why AI ?
  • Goal Of AI
  • What comprises to AI
  • Advantage and Disadvantage of AI
  • Applications of AI
  • History of AI
  • Types of AI
  • Type-1 Narrow general strong
  • Type-2 Reactive machine Limited memory theory of mind self awareness
  • Type of AI Agents
  • PEAS Representation P: Performance measure E: Environment A: Actuators S: Sensors
  • Agent Environment in AI
  • Features of Environment in AI
  • AWS Sage Maker - Setup and Project Deployment
  • Reinforcement using AWS OpenAI Gym (Q-Learning)
  • GAN's, AWS DeepComposer
  • Project deployment of RASA chatbot using AWS
  • More application in AWS (Polly, Lex, Rekognition, Transcribe, Translate)
  • Episodic vs sequential
  • Known vs Unknown
  • Episodic vs sequential
  • Accessible vs Inaccessible
  • Introduction to AWS SageMaker
  • Set up Amazon SageMaker
  • Onboard to Studio
  • Notebook instances
  • Automated Machine Learning
  • Label Data
  • Create, Store and Share features
  • Training
  • Inference
  • Marketplace
  • security
  • deployment & manage
  • AWS A2I
  • Introduction to reinforcement
  • AWS OpenAI Gym (Q-Learning)
  • GANs
  • AWS DeepComposer
  • AWS OpenAI Gym (Q-Learning)
  • Rasa chatbot development and deployment using AWS
  • More in AWS
  • Amazon Polly
  • Amazon Sagemaker
  • Amazon Lex
  • Amazon Rekognition
  • Amazon Comprehend
  • Amazon Transcribe
  • Amazon Translate

Programming Languages & Tools Covered

Excel
Tablue
MySQL
Python
R-Tool_website
R-studioTool_website
Jupyter
Scikit Learn
Tenserflow
Keras
NLTK
Open-CV
Statsmodel
Surprise
AWS
Hadoop
SQOOP
Flume
Apache-Pig
Hive
Apache-Spark

Case Studies

Telecom Customer Defection Analysis
Telecom Customer Defection Analysis
itvedant
itvedant

Customer churn, also known as customer defection, is the loss of clients or customers. Telephone service companies often use customer churn analysis and customer churning rates as one of their key business metrics. In this project, we will analyze telecom data and predict the chance of customer defection using various Machine Learning Classification Algorithms.

itvedant
Twitter Data Analysis
Twitter Data Analysis
itvedant
itvedant

Using the concepts and tools of the Big data, we will collect and store a large amount of data from tweets. This data will be further used for analyzing and extracting sentiments using Natural Language processing techniques.

itvedant
Image recognition
Image Recognition
itvedant
itvedant

Using the concepts of computer vision, the machine will identify objects placed under the camera. Similar concepts will be used for face detection and authentication.

itvedant
Movie recommender
Movie Recommender
itvedant
itvedant

Using the concepts of the recommender system, the application will be able to recommend movies to the user depending on past experience and the customer's personal choice.

itvedant
Stock market analysis
Stock Market Analysis
itvedant
itvedant

Using the concepts of time series analysis, the application will be able to predict future patterns of stock by analyzing the previous patterns. This project will also use various visualization techniques for visualizing the stock pattern.

itvedant
Credit card fraud detection
Credit Card Fraud Detection
itvedant
itvedant

It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.

itvedant
Uber ride Data Analytics
Uber Ride Data Analytics
itvedant
itvedant

You are a cab rental start-up company like Uber and You have successfully run the pilot project and now want to launch your cab service across the country. You have collected the historical data from your pilot project and now have a requirement to apply analytics for fare prediction. You need to design a system that predicts the fare amount for a cab ride in the city.

itvedant
Insurance claim detection
Insurance Claim Detection
itvedant
itvedant

Insurance companies take risks over customers. Risk management is a very important aspect of the insurance industry. Insurers consider every quantifiable factor to develop profiles of high and low insurance risks. Insurers collect vast amounts of information about policyholders and analyse the data.As a Data scientist in an insurance company, you need to analyse the available data and predict whether to sanction the insurance or not

itvedant
Telecom Customer Defection Analysis
Telecom Customer Defection Analysis
itvedant
itvedant

Customer churn, also known as customer defection, is the loss of clients or customers. Telephone service companies often use customer churn analysis and customer churning rates as one of their key business metrics. In this project, we will analyze telecom data and predict the chance of customer defection using various Machine Learning Classification Algorithms.

itvedant
Twitter Data Analysis
Twitter Data Analysis
itvedant
itvedant

Using the concepts and tools of the Big data, we will collect and store a large amount of data from tweets. This data will be further used for analyzing and extracting sentiments using Natural Language processing techniques.

itvedant
Image recognition
Image Recognition
itvedant
itvedant

Using the concepts of computer vision, the machine will identify objects placed under the camera. Similar concepts will be used for face detection and authentication.

itvedant
Movie recommender
Movie Recommender
itvedant
itvedant

Using the concepts of the recommender system, the application will be able to recommend movies to the user depending on past experience and the customer's personal choice.

itvedant
Stock market analysis
Stock Market Analysis
itvedant
itvedant

Using the concepts of time series analysis, the application will be able to predict future patterns of stock by analyzing the previous patterns. This project will also use various visualization techniques for visualizing the stock pattern.

itvedant
Credit card fraud detection
Credit Card Fraud Detection
itvedant
itvedant

It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.

itvedant
Uber ride Data Analytics
Uber Ride Data Analytics
itvedant
itvedant

You are a cab rental start-up company like Uber and You have successfully run the pilot project and now want to launch your cab service across the country. You have collected the historical data from your pilot project and now have a requirement to apply analytics for fare prediction. You need to design a system that predicts the fare amount for a cab ride in the city.

itvedant
Insurance claim detection
Insurance Claim Detection
itvedant
itvedant

Insurance companies take risks over customers. Risk management is a very important aspect of the insurance industry. Insurers consider every quantifiable factor to develop profiles of high and low insurance risks. Insurers collect vast amounts of information about policyholders and analyse the data.As a Data scientist in an insurance company, you need to analyse the available data and predict whether to sanction the insurance or not

itvedant

Slide to Know Your Salary

3 LPA
0 Yrs 2 yrs 4 Yrs 6 Yrs 8 Yrs
20 LPA

Job Roles You Can Apply for

Applied Data Scientist
NLP Engineer
ML Engineer
Big Data Consultant
Data Science Engineer

Our Certifications

Master Certification in Data Science and & Analytics
Itvedant Certificate
The Master Certification program of Data Science & Analytics prepares you for the heavyweight title – Data Scientist. Not just that along with the master certification of Data Science & Analytics you shall be given 13 course module completion certificates at every check-point clearance if you are effective in meeting the Itvedant® Assessment Standards.And yes did we say you can easily clear the Google TensorFlow Exam with our guidance ? Look next
Master certification in Data science and analytics
Google Certification in Data Science and & Analytics
Google Certificate
Itvedant prepares you for the Tensorflow Certification Program ! The Tensorflow Certification is recognised globally and your skills in Machine Learning is assessed by a company known by everyone ” Google® “
google tensorflow certification
Microsoft Certification in Data Science and & Analytics
Microsoft Certificate
Itvedant prepares you for the Microsoft Certification Program ! The Microsoft Certification is recognised globally and your skills in Python is assessed by a company known by everyone ” Microsoft® “
Microsoft Certification

FAQ's

What is the minimum qualification required to enroll into Data Science with AI & AWS ?

Individuals with a minimum qualification of 12th can enroll into our Data Science with AI & AWS.

What is the duration of the course ?

The duration of the course is 12 Months.But the duration of the course solely depends on the number of modules you choose to learn.

What happens if I miss a session?

You needn’t worry about missing a session, our dedicated Relationship manager, would help you with anything related to administration. The Relationship manager will arrange a session with trainers in place of the missed one.

Can I pay my total course fee in EMI’s ?

Yes, you can avail No Cost EMI’s (No Interest) at Itvedant, for which you are supposed to pay the 25% of the fees as first down payment and the remaining fees in 9 Months instalments.

What kind of salary can I expect after the successful completion of my Data Science with AI & AWS ?

A fresher in Data Science with AI & AWS would draw a salary in a range of 3-15LPA at Itvedant.

When can I expect to receive placement calls and how long ?

We are equipped with a very strong placement wing who make sure you are placed. You start receiving placement calls right after completing 60% of your course. You may receive unlimited placement calls at Itvedant. We make sure you get placed!

Is any certification granted at the end of the Course ?

Post successful completion of the Course, a Masters in Data Science with AI & AWS would be granted from Itvedant along with Microsoft Certificate

Is the course Masters in Data Science with AI & AWS alone enough to get hired ?

Yes, our unique modules in Data Science makes you Industry ready right after the course and we assure 100% placement assurance

What am I supposed to bring to the Institute? Are computers provided?

You needn’t bring anything, in particular, you will be provided with individual laptops and study materials at Itvedant.

Get a Job In

Accenture
Airtel
Capgemini
Deloitte
HP
IDBI Bank
Jio
Max life
Reliance industries
TCS

Alumni Testimonials

Thank you for contacting us !

Our Team will get in touch with you soon or call 9205004404 now to get answer for all your queries !

Like Our Facebook page to be up to date in industry !

Close