Certified AI & ML BlackBelt Plus Program

Power ahead in your AI & ML Career

  • 1:1 Mentorship with Guided Projects
  • Comprehensive & Personalized Learning Path
  • Dedicated Interview Preparation & Placement Support
  • 200+

    Hours of Learning

  • 1:1

    Mentorship Sessions

  • 50+

    Real-World Projects

  • 100%

    Placement Assistance

  • 4.6

    Average Mentorship Rating


FLAT 25% OFF + Microsoft Azure Course Free

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Use Coupon Code: CYBERSAFE

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How BlackBelt Plus prepares you for AI & ML Career?

1:1 Mentorship with Guided Projects

  • Weekly Mentorship Calls
  • Work on Industry Projects under the guidance of experts
  • Get Personalized Recommendations

Comprehensive & Personalised Learning Path

  • Cutting Edge Curriculum
  • Work on Real Life Projects
  • Personalised for your goals

Prepares you for AI and ML Jobs

  • Learn industry Relevant Skills
  • Build your Profile
  • Resume and Interview Preparation

Succeed with 1:1 Personalised Mentorship

Succeed with Personalised Roadmap

Get a personalised roadmap to succeed in your AI & ML goals

1:1 Mentorship Calls with Guided Projects
  • Weekly Mentorship Calls
  • Work on 10+ Guided Projects with experts
  • Rating - 4.92 / 5.00
  • Doubts and Queries - Technical
  • Industry Experienced Mentors
Assistance in Job Preparation

Mentors to guide you how to get your dream job

  • Resume & Interview Preparation
  • Profile Building - Linkedin , Github , Analytics Vidhya Community
  • 3 Mock Interviews

What does it mean to be BlackBelt Plus Certified?

BlackBelt Plus Certified Data Scientists can create cutting edge solutions and become pioneers in the space of Artificial Intelligence, pioneers who will develop AI Applications that will revolutionize life as we know it.

  • Mastery in 22+ Tools
  • Expertise in Data Science, Machine Learning, Deep Learning and Data Engineering Subjects
  • Ability to solve real world industry problems

The Ultimate Data Science Industry Conference

Be a part of 8+ full-day online AIConf and experience 65+ hours of live Industry conferences with the Experts!
Here's how a day at AIConf will look like...
Live Industry Sessions
  • Hear industry experts from different domains speak about applications and use cases around data science
  • Live Q&A
Hack Sessions
  • Multiple sessions to allow you to see the problem-solving approach by Industry experts
  • Live Q&A
Panel Discussions
  • Watch top AI Industry leaders, discuss the future of AI and ML in the invigorating panel discussion.
  • Live Q&A


20+ Modules starting from basics like Excel to the most cutting edge techniques of Machine Learning, Deep Learning, NLP and Data Engineering required by every Data Scientist

Master Microsoft Excel

Explore Important Formulas and Functions

Create Charts and Visualizations using MS Excel

Get Familiar with MySQL

Creating and updating reports in SQL

Performing Data Analysis using SQL

Explore Python for Data Science

Important libraries and functions in Python

Reading file and manipulating data in python

Working with data frames, lists, and dictionary

Use Matplotlib and Seaborn for data visualization

Creating charts to visualize data and generate insights

Univariate and Bivariate analysis using python

Perform Statistical Analysis on real-world datasets

Build and Validate Hypothesis using statistical tests

Generating useful insights from the data

Importing and working with different kinds of data in Tableau

Build bubble charts, geo-location charts, and many others

Learn to create Dashboards in Tableau

Master storyboarding in Tableau

Learn to create engaging presentations

Perform feature engineering in Tableau

Become familiar with data manipulation in Tableau

Loading datasets and establishing table relationships in PowerBI

Work with different type of charts and dashboards in PowerBI

Working with Map visualizations and other advanced charts with drill down functionalities in PowerBI

Working with power query for data manipulation in PowerBI

Writing DAX expressions in PowerBI

Learn Important Machine Learning concepts

Perform data cleaning and Preprocessing

In-depth understanding of Basic ML models

Linear Models, Decision Tree, k-NN

Math Behind each Machine Learning Algorithm

Building Classification and Regression Models

Hyperparameter Tuning to improve model

Solving real-world business problems using Machine Learning

Learn the art of Feature engineering

Feature Generation from time-series data

Automated Feature Engineering Tool

Concept of dimensionality reduction

Feature Selection and Elimination Techniques

Detailed Understanding of Principal Component Analysis (PCA)

Concept of Factor Analysis

Explore the Advanced ML concepts and Algorithms

Use Ensemble Learning Techniques (Stacking and Blending)

Understand and Implement Bagging and Boosting Algorithms

Learn to handle Text data and Image Data

Working with structured and unstructured data

Dealing with unsupervised learning problems

Clustering Algorithms including k-means and Hierarchical clustering

Dealing with ambiguous business problems

Structure a business problem into a data science problem

Understanding the Machine Learning Lifecycle

Key Frameworks for each stage in ML Lifecycle

Present analysis and business insights in an impactful manner

Communicate ideas and insights to the stakeholders

Important concepts of Deep Learning

Working of Neural Network from Scratch

Activation Functions and Optimizers for Deep Learning

Understand Deep Learning architectures (MLP, CNN, RNN and more)

Explore Deep Learning Frameworks like Keras and PyTorch

Learn to tune the hyperparameters of Neural Networks

Build Deep Learning models to tackle real-life problems

Get familiar with the world of Computer Vision

Transfer Learning for Computer Vision

Work with popular Deep Learning Framework - Pytorch

Learn State-of-the-art Algorithms like YOLO, SSD, RCNN and more

Work on different types of problems

Build Face Detection and Pose Detection Models

Advanced CV Problems like Image Segmentation and Image Generation

Understand how GANs work

Handling Text Data (Cleaning and Pre-processing)

Use Spacy, Rasa and Regex for exploring and processing text data

Information Extraction and Retrieval from text-based data

Understand Language Modelling

Learn Advanced Feature Engineering techniques

Build NLP models for Text Classification

Understand Topic modelling

Work on Industry Relevant Projects

Understand the concept of Sequence-to-Sequence Modeling

Build a Deep Learning Model for Language translation in PyTorch

Learn to use Transformers library by Huggingface

Use Transformers to perform transfer learning in NLP

Build and Deploy your own chatbot

Learn to work with audio-based data

Build a voice assistant system using Deep Learning

Recommender Systems in industry

Detailed Taxonomy of types of Recommender Systems

Collaborative Filtering Methods

Content-Based Recommender Systems

Knowledge-Based & Hybrid Recommender Systems

Market Basket Analysis & Association Rules

Evaluation of Recommender Systems

Build Book recommender System and other real-life projects

Important concepts of Time Series Forecasting

Machine Learning techniques for Time Series forecasting

Validation techniques for Time series data

Framework to evaluate Time Series Models

Exponential Smoothing Methods for forecasting

Reading ACF and PACF plots

Tuning Parameters for ARIMA


Deep Learning for time series

Solve Real-world business problems

Understanding the different roles in Data Science

Dos and Don'ts for Resume Building

Tips and strategies to build the perfect resume

Preparing for Data Science Interviews

Understanding the important skills required

How to build your digital Presence

Tips and Tricks to Ace Data Science Resume

List of Interview Questions for Data Science

Overview of Python Basics

Documentation and Formatting

Testing and Debugging

Exception Handling and Assertions

Python Standard Libraries

Functional Programming

Object Oriented Programming

Working with Shell/Terminal Commands

Introduction to Version Control and Github

Connecting with DataBases

Understanding NoSQL Databases

Querying in MongoDB

Aggregation Pipeline

Indexing in MongoDB

Replication and Sharding

Introduction to Data Engineering

Demand for Data Engineers

Roles & Responsibilities of Data Engineer

Big Data and its applications

Distributed Systems

Components of Apache Hadoop

Hadoop Ecosystem

Introduction to Hadoop 1.x

Working and Archutecture of MapReduce

Introduction to Hadoop 2.x

Understanding HDFS and Components

Working and Architecture of YARN

Hadoop 2.x vs Hadoop 3.x

Overview of Hive

Creating databases and tables in Hive

Types of Hive tables

Hive Query Language

Joins in Hive

Partitioining and Bucketing

File Formats and SerDes in Hive

Views in Hive

Introduction to Hadoop and Spark Ecosystem

Deep Dive into Spark Ecosystem

RDDs in Spark

DataFrames in Spark

Spark SQL

Data Wrangling with Spark

Jobs, Stages and Tasks in Spark

Advanced Programming in Spark

Machine Learning with Spark ML

Challenges with traditional stream processing systems


Spark Streaming Architecture

Spark Streaming Data Sources

Transformations on DStreams

Stateful and Stateless Transformations

Overview and aspects of Model Deployment

Deploying Machine Learning models using Streamlit

Introduction to Amazon Web services

Deploying and Machine Learning Deep Learning models using AWS

Understanding Amazon Sagemaker

Model Deployment using Sagemaker

APIs for Model deployment

  • 50+ Projects
  • 200+ Hours
  • 22+ Tools
  • 35+ Assignments
  • 105+ Mentorship Sessions

Tools You will Master in AI & ML BlackBelt Plus

Reinforce Your Learning with 10+ Guided Projects

Work on 50+ real world projects including 10+ guided projects with industry experts and mentors. Unlock your first guided project on your each course completion.
Movie Recommender System

Movie Recommender System

Learning Objectives:

-Learning user watching patterns to provide relevant suggestions
-Enhancing user experience for online streaming services

Business Solving Similar Problems:

Netflix, Amazon Prime, Voot

Guided Project
Auto Correct

Auto Correct

Learning Objectives:

-Learn to work and pre-process text data
-Building an end to end autocorrect model

Business Solving Similar Problems:

Search Engines, Messaging platforms


Face Detection

Learning Objectives:

-Learn to detect faces from image Implementation of state of the art models like RetinaNet, YOLO

Business Solving Similar Problems:

Smart ATMs, User friendly check-ins at Airports

Guided Project

WebTraffic Prediction

Learning Objectives:

-Learn working with Time Series Data
-Using Deep Learning models for time series forecasting

Business Solving Similar Problems:

Publishing and advertising processes of different websites

Industry Experts & Mentors


Kunal Jain

Founder & CEO, Analytics Vidhya

Sunil Ray

Chief Content Officer at Analytics Vidhya

Anand Mishra

Chief Technical Officer at Analytics Vidhya

Pranav Dar

Sr Editor & Data Scientist at Analytics Vidhya

Hear from our Students

Transition from System Engineer to Consultant at Fractal

I chose the Blackbelt+ program over several online PGDP programs. This program is meticulously designed with all the necessary concepts and topics from the vast ocean of Data science to become a full-stack Data Science Practitioner. As part of Placement Assistance, I also got an interview opportunity from Analytics Vidhya. Enrolling in this program is one of the best decisions I've made and enabled me to transition into the Data Science field as a Consultant in Fractal

Transition from Application Development Analyst to Associate: R&D at Axtria

The BlackBelt Plus program provides a wide range of curriculum in a structured manner which is lacking in most of the online courses. The program not only gave me structured content with a proper roadmap but also the 1:1 mentorship calls proved vital in clearing my doubts related to courses or careers. Courses on Career Acceleration and personalized mock interviews helped me to gain the soft skills and confidence required to crack the interviews and make a transition into the Data Science domain..

Great course to enter into Data Science field!!

This course not only taught me how to step into the vast field of data science but also helped me develop an aptitude for it!

Start your journey to success with a personalised Roadmap

It will be personalised after your first mentorship call
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    Develop ML Skill

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    Develop Problem Solving Skill

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    Work on Hackathon & Projects

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    Develop Storytelling Skills

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    Build AI & ML Portfolio

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    Start Deep Learning Journey

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    Learn Natural Language Processings

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    Learn Computer Vision

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    Learn Advanced Python & Software Engineering

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    Deploy ML/DL models

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    Master Apache spark

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    BlackBelt Plus Certification

Program Fees


(Inclusive of taxes )

1:1 Personalised Attention

  • Personalised Success Roadmap
  • 105+ Technical mentorship sessions
  • 3 mock interviews

Comprehensive Curriculum

  • 200+ Learning Hours
  • Work on 50+ Real-world Project
  • Master 14+ Cutting Edge Tools

100% Placement Assistance

  • Multiple personalised mock interviews & feedback
  • Get your resume noticed by our hiring partners
  • Dedicated Career Acceleration Team


Get BlackBelt Plus Certified By Analytics Vidhya Share your Achievement with the World

  • Earn Your Certificate
  • Share Your Achievement

Money Back Guarantee!

BlackBelt Plus program comes with 7 days no questions asked Money back Guarantee. If the program is bought in pre-launch offer or on discounted price, then the fee paid is non-refundable. For more T&C, click here


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