Mastering Machine
Course for
the Industry

Mastering Machine Learning
under the Certified AI & ML Black Belt Plus Program

  • Learn Python from basic to advanced in this Machine Learning Course
  • Solve real-world Machine Learning Projects
  • Mentorship for Machine Learning Interview
  • Applied Machine Learning Course that prepares you for the industry.
  • Get a Machine Learning Certification from Analytics Vidhya
For Enquiries:

+91 8368808185

  • 500+

    Hours of Learning

  • 1:1

    Mentorship Sessions

  • 50+

    Real-World Projects

  • 100%

    Placement Assistance

  • 4.6

    Average Mentorship rating

Why get a Machine Learning Certification?

  • Machine Learning is reshaping and revolutionizing the world and disrupting industries and job functions globally. It is no longer a buzzword - many different industries have already seen disruptions from Machine Learning. And all of them are searching for candidates with credible Certification from a good Machine Learning Course
  • In this age of machine learning, every aspiring data scientist is expected to upskill themselves in machine learning techniques & tools and apply them to real-world business problems. And there is nothing better than the Applied Machine Learning Course for Beginners with certification from Analytics Vidhya
  • Machine Learning is disrupting the future. Are you ready for it?

About the Machine Learning Course

Get ready to to begin your journey with the best Machine Learning Course for beginners in the town-

About the Machine Learning Course for beginners under the Certified AI & ML Blackbelt Plus Program

This Machine Learning course for beginners provides you all the tools and applied machine learning techniques you need to solve business problems. We will cover the basics of machine learning, how to build machine learning models, improve and deploy your machine learning models as a part of this Machine learning certification under the Certified AI & ML Blackbelt Plus Program

Learning objectives of this Applied Machine Learning Course for beginners

This Applied Machine Learning course is a treasure house of all ML concepts under one roof. You will be learning the following things in this course-

  • Understand how Machine Learning and Data Science are disrupting multiple industries today
  • Linear, Logistic Regression, Decision Tree and Random Forest algorithms for building machine learning models
  • Understand how to solve Classification and Regression problems in machine learning
  • Ensemble Modeling techniques like Bagging, Boosting, Support Vector Machines (SVM), and Kernel Tricks.
  • Learn dimensionality reduction techniques like Principal Component Analysis (PCA) and t-SNE
  • Evaluate your machine learning models and improve them through Feature Engineering
  • Learn Unsupervised Machine Learning Techniques like k-means clustering and Hierarchical Clustering
  • Learn how to work with different kinds of data for machine learning problems (tabular, text, unstructured)
Which skills will I gain after this Applied Machine Learning Course?

By the end of this machine learning certification, you will become an expert in the following-

  • Python for Machine Learning and Data Science
  • Statistics
  • Data Visualization and Exploratory Data Analysis
  • Machine Learning Algorithms (Regression, Decision Trees, Random Forest, Clustering SVM)
  • Ensemble Modeling (Bagging, Boosting, Support Vector Machines (SVM) and Kernel Tricks)
  • Dimensionality Reduction(PCA)
What are the prerequisites for this Machine Learning Course for beginners?

This Machine Learning certification requires no prior knowledge about Data Science or any tool.

Who is this Machine Learning Course for?

This Machine learning certification has been designed for all Machine Learning enthusiasts from all walks of life. So even if you are a Machine learning beginner, there is nothing to worry about. We have curated all the content for each course in a way that’s easy-to-digest for people coming from a non-technical and non-machine learning background as well. The AI & ML BlackBelt Plus program is one of the best machine learning (python) courses available in the industry.

I want to learn and master Machine Learning. Is this Applied Machine Learning Course for me?

Yes. This data science and machine learning course is for people who want to start their journey in Machine Learning and go from beginner to advanced in the field of data science. The AI andML Blackbelt Plus course consists of all the modules that you will ever need to become a successful Machine Learning Engineer or a Data Scientist.

How Can You Excel in Machine Learning?

You don’t need a PhD to master the art of Machine Learning. Although you must be aware of the important topics mentioned here -

  • Python Programming Language
  • EDA and Statistics
  • Knowledge of Tools like Pandas, NumPy, Scikit Learn, and more
  • Data Visualization
  • Machine Learning Algorithms - Basic to Advanced

Certified AI & ML
BlackBelt Plus

Power ahead in your AI & ML Career
  • 1:1 Mentorships with Industry Practitioners
  • Comprehensive & Personalised Learning Path
  • Dedicated Interview Preparation & Support

How BlackBelt Plus Machine Learning Certification prepares you for a Career in ML?


Comprehensive & Personalised ML Learning Path

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

Prepares you for Machine Learning Jobs

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

1:1 Mentorship with Industry Practitioners

  • 105+ Mentorships
  • Get clarity on each and every ML concept in this Machine Learning course
  • Get personalised recommendations for career in NLP

What will you learn in this Machine Learning Course?

This Online Machine Learning course for beginners under the AI and ML Blackbelt Plus program will provide you with the knowledge of tools and techniques to master Machine Learning using python. Here’s what you will learn in the Machine Learning certification -

  • Understand how Machine Learning is disrupting multiple industries
  • Basic Machine Learning algorithms.
  • Solve Classification and Regression problems in machine learning
  • Master advanced Ensemble Modeling techniques
  • Learn dimensionality reduction techniques
  • Machine Learning Model evaluation & Feature Engineering
  • Unsupervised Machine Learning Techniques
  • Work with different kinds of data for machine learning problems

Succeed with 1:1 Personalised Mentorship

Succeed with Personalised Roadmap

Get a personalised roadmap to succeed in your NLP career

1:1 Mentorship with Industry Practitioners
  • 75+ Mentorship calls
  • Rating - 4.92 / 5.00
  • Doubts and Queries - Technical
  • Industry Experienced Mentorsa
Assistance in Job Preparation

Mentors to guide you how to get your dream job

  • Resume & Interview Preparation
  • Profile Building - Linkedin , Github , Analytics Vidhya Community
  • 2 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 Subjects
  • Ability to solve real world industry problems


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

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

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

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

Machine Learning Course Tools AWS
Machine Learning Course Tools Keras
Machine Learning Course Tools Pytorch
Machine Learning Course Tools  sckit learn
Machine Learning Course Tools Power BI
Machine Learning Course Tools Spacy
Machine Learning Course Tools Excel
Machine Learning Course Tools  Rasa
Machine Learning Course Tools Flask
Machine Learning Course Tools Stream lit
Machine Learning Course Tools Amazon segamaker
Machine Learning Course Tools Dask
Machine Learning Course Tools SQL
Machine Learning Course Tools Tableau
Machine Learning Course Tools Spark
Machine Learning Course Tools ML BOX
Machine Learning Course Tools Scikit image
Machine Learning Course Tools AWS
Machine Learning Course Tools Keras
Machine Learning Course Tools Pytorch
Machine Learning Course Tools  sckit learn
Machine Learning Course Tools Power BI
Machine Learning Course Tools Spacy
Machine Learning Course Tools Excel
Machine Learning Course Tools  Rasa
Machine Learning Course Tools Flask
Machine Learning Course Tools Stream lit
Machine Learning Course Tools Amazon segamaker
Machine Learning Course Tools Dask
Machine Learning Course Tools SQL
Machine Learning Course Tools Tableau
Machine Learning Course Tools Spark
Machine Learning Course Tools ML BOX
Machine Learning Course Tools Scikit image

Reinforce Your learnings with 50+ projects

Doing projects is one of the most essential step to apply your learning and showcase in your resume.
Writing code is one thing but writing it efficiently, well that requires practice.
Machine Learning Course Projects NYC Taxi Trip Duration Prediction

NYC Taxi Trip Duration Prediction

Learning Objectives:

Understand the importance of Data Exploration Learn the power of Feature Engineering to improve your models.

Business Solving Similar Problems:

Uber, Lyft, Ola

Machine Learning Course Projects Customer Churn Prediction

Customer Churn Prediction

Learning Objectives:

Perform Data Exploration to understand relationship between variables Learn to implement Machine Learning Models

Business Solving Similar Problems:

Various Banking Institutions

Machine Learning Course Projects Webpage Classification

Webpage Classification

Learning Objectives:

Working with Text Data Cleaning and Preprocessing text corpus Implementing ML Models for text classification

Business Solving Similar Problems:

Various Banking Institutions

Machine Learning Course Projects Malaria Detection from blood cell Images

Malaria Detection from blood cell Images

Learning Objectives:

Working with Image Data Implementing Deep Learning Models for Image Classification

Business Solving Similar Problems:

Healthcare Industry

Industry Experts & Mentors for the Machine Learning Course

kunal jain

Kunal Jain

Founder & CEO, Analytics Vidhya
sunil ray

Sunil Ray

Chief Content Officer at Analytics Vidhya
anand mishra

Anand mishra

Head Of Engineering at Analytics Vidhya
pranav dar

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

Program Fees


(Inclusive of taxes )

1:1 Personalised Attention

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

Comprehensive Curriculum

  • 200+ Learning Hours
  • Work on 50+ Real-world Projects
  • Master 17+ Cutting Edge Tools

Go from Beginner to Master

  • No pre-requisites required
  • Work on NLP and Deep Learning Projects

Machine Learning Online Certification

Earn your AI & ML Blackbelt Plus Program Certificate

Our AI and Machine Learning training is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.

Differentiate yourself with an AI Certificate

Machine Learning skills you've gained working on projects, simulations, case studies will set you apart and ahead in the industry.

Share your achievement

Talk about your Blackebelt Plus certification on social media and boost your resume.


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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