Certificate Program in

Artificial Intelligence and Machine Learning

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Bachelor’s degree

Application deadline

To be announced

A Career in XR Awaits

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Our recipe for your success

Batch starts

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11 months

Total effort

654+ hrs

Case-based learning with 5+ mini projects tied into the program

Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered

7+ Industry projects and case studies

Experience the difference with live learning

Real time engagement withlive classes

Learn at your pace, on your schedule

Enhanced outcomes through more than 80% live and experiential learning

Our holistic learning philosophy

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Live learning

Interactive classes with industry experts for hands-on learning

Case studies

Real-world tasks to solidify knowledge and prep for industry challenges.

1:1 counselling

Personalized mentorship for career navigation and professional decisions.

Seasoned faculty

Guidance from leading industry experts to ensure top-tier learning.

Capstone projects

Final projects that blend learning with real impact in your field.

Doubt clearing sessions

Targeted sessions to ensure clarity and readiness for next steps.


Python Programming

  • Installation and Set-up
  • Python Basics - Syntactics,Variable Types, Operators
  • Functions - Built-in, Library and Custom, Arguments
  • Data Structures and Operations: Lists, Tuple
  • Data Structures and Operations: Dictionaries
  • For/While Loops, Conditional Statements
  • Nested Loops and Nested Conditions
  • File Handling - I/O functions, open() read, write, append , with
  • Handling json and xml files and using csv module

  • Doing version control on local sytem, branching, creating remote repository on github, working collaboratively on github, raising PR, merging PR

  • Introduction to Pandas and Numpy Modules
  • Pandas Basics - Data File Handling, Row/Columns Handling, Slicing, Drop, Sort, New Variable Creation, Observing Frequency Count
  • Pandas Advanced: Multiple Datasets Handling, Merge/Append, Multivariable Groupby/Crosstab Summaries
  • Working with Datetime Data and Time Series Data
  • Working with Indexes and Multi-level Indexing

  • Importance of Visualizing Data through Charts
  • Types of Charts and their Best Uses
  • Basics of Visualization in Python Using Matplotlib and Seaborn:
  • Components of a Plot, Subplots, Functionalities of a Plot
  • Plotting Data Distributions,Univariate distributions

  • Databases - Schema, Table, Relations.
  • Basics of SQL, SQL commands - SELECT, FROM, WHERE, AND, OR, NOT, Pattern matching, sorting, Orderby, Comments and Operators
  • Group by, aggregate functions (MIN,MAX,SUM,AVERAGE,COUNT), having CRUD operations: Create and Drop Data bases, Create and Drop TablesConstraints (Primary key, Foreign Key, Unique key, Not Null, Default and CHECK)
  • Joins (inner/left/right/full)
  • Nested Queries
  • Windows Analytical Functions (Aggregate, Ranking, and Windows Analytical Functions)
  • Speed up Queries Using Indexes
  • In this module, learners will explore the different frameworks to create the business model for the product.
  • Various Types of Indexes

  • Doing sanity checks on data
  • Finding relationship between continous variables
  • Finding relationship between categorical variables
  • Finding relationship between a categorical and continous variable

  • Identifying scenarios where a binomial or a poisson distribution can be used
  • Enumerating the values that a random variable can take
  • Computing probability mass using binomial or poisson distribution

  • Be able to formulate correct form of null and alternate hypothesis when underlying random variable is binomial or poisson
  • Be able to arrive at the correct formulation of p-value
  • Be able to use CLT to tackle scenarios involving large sample means

  • Be able to correctly identify where to use ANOVA, 2 sample t test or chi square test of factor association.
  • Be able to formulate correct null and alternate hypothesis for each of the tests
  • Be able to arrive at a business decision once the test has been done

  • Undertand the idea of predictor variables and target variables.
  • Outline how a trained model is to be validated
  • Identify regression, classification and clustering tasks

  • OLS Regression Model
  • Predicting continuous variable
  • Using Gradient Descent for Linear Regression, Model evaluation using loss functions, RMSE, R-Square, Stochastic Gradient Descent

  • Predicting a binary variable, interpreting model output, using Python to create a logistic model – using statistics and machine learning methods
  • Checking model diagnostics
  • Concept of Confusion Matrix and Computing Accuracy Metrics, ROC, AUC, doing kfold cross validation

  • Decision Trees
  • Checking model diagnostics
  • Bagging and Boosting Techniques
  • Random Forest
  • OOB
  • Hyperparameter tuning using GridSearch

  • Introduction to clustering
  • Distance norms
  • K-means clustering, Elbow method, Silhouette Score, Profiling

  • Tfidf featurization and text classification
  • Using spacy to handle classical tasks such as lemmatization, pos tagging, dependency parsing
  • Building topic models and discovering key-terms

  • Building a model training pipeline.
  • Building model as an api service.

  • Introduction to Neural Networks: Introduction to Neuron, Activation functions - sigmoid, tanh, relu, etc Loss functions - cross-entropy loss, MSE, etc Optimization Techniques - Gradient Descent, Batch Gradient, Mini-batch Gradient and Stochastic Gradient etc. Building simple MLP using numpy

  • Building datasets and dataloaders
  • Defining custom models
  • Using early stopping and logging
  • Using different types of optimizers

  • Word vectors and embedding layers
  • Sequential Processing using RNN and LSTM Layers
  • Attention mechanism and encoder-decoder architecture
  • Using hugging face to build bert based models

Unlock valuable insights

5-star rating by 97% of students.

Discover the outcomes of the program.

Explore the custom-curated learning path.

Launch projects, leap forward

Environmental analysis

Environmental analysis

Examine environmental data, encompassing metrics such as air or water quality, to comprehend the influence of human activities on our surroundings and pinpoint areas requiring enhancement and mitigation efforts.

E-Commerce Website

E-Commerce Website

Interrogate data derived from e-commerce platforms, including sales trajectories, customer behavior patterns, and product popularity, with the objective of identifying potential avenues for refinement and optimization.

Financial analysis

Financial analysis

Analyze financial data, such as stock prices and investment portfolios, to identify trends and patterns that can inform investment decisions.


In collaboration with

National Skill Development Corporation

NSDC has trained over 5.2 million students, leveraging a vast network of partnerships.

Participates in WorldSkills to showcase and enhance the international standards of Indian skills​.

Collaborates with global tech leaders like Google and Microsoft to advance digital skills training.

Get certified

Leveraging Snapchat's expertise in pioneering augmented reality technologies and Unreal Engine's leadership in immersive virtual experiences, this certificate sets you apart in extended reality.

* Certificates are indicative and subject to change

Our faculty, your mentors

Soumita Mukherjee

Soumita Mukherjee


Faculty, Hero Vired | 14+ years of corporate experience


A globally recognized expert passionate about bridging the academic and the business world & known for his work on customer-centric digital transformation.

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Ben Campose

Ben Campose


Director, Act Global Trainers India | 30+ years of experience


Ben has over 30 years of coaching experience in Sales, Leadership and professional development across industries.

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Start your learning journey, today

Application Submission

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Certificate Program in

Artificial Intelligence and Machine Learning

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EMI Starts at

₹3,565 / month

Price: ₹1,25,000 + GST

What you will get:

Case-based learning with 5+ mini projects tied into the program

Python, PyTorch, NumPy, Matplotlib, and Seaborn are the essential tools covered

7+ Industry projects and case studies


11 Months

Apply by

To be announced

Frequently Asked Questions

What is Artificial Intelligence and Machine Learning course all about?

An AI & ML course focuses on teaching you the different concepts and technologies associated with the field. An artificial intelligence and machine learning program will cover tools like Pandas, NumPy, Seaborn, Git, PyTorch, and more.

An artificial intelligence and machine learning program can help you develop skills and knowledge to stay relevant in the industry. It will prepare you for high-paying roles like computer vision engineer, AI engineer, machine learning engineer, and more.

The artificial intelligence and machine learning course will teach you to work with Python, Pandas, Git, NumPy, Seaborn and more to design technologies for the future. You will receive knowledge about different concepts like data visualization, SQL foundations, predictive modelling, and more.

View more

Hero Vired logo
Hero Vired is a premium LearnTech company offering industry-relevant programs in partnership with world-class institutions to create the change-makers of tomorrow. Part of the rich legacy of the Hero Group, we aim to transform the skilling landscape in India by creating programs delivered by leading industry practitioners that help professionals and students enhance their skills and employability.

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