Last date to Enroll – 12th May, 2023

About     Program Highlights     Topics     Certification     Pedagogy     Curriculum     Faculty     Fee Structure

About the program

The Business Application of Artificial Intelligence program from Innosential, in association with Dayananda Sagar university, equips learners with the knowledge and expertise to navigate the impending AI and ML revolution, including AI and ML Engineer certification from Amazon, Google, and Microsoft.

Taught by experts from academia, AI geniuses who have set world-leading AI systems, and practicing data scientists, the course uses Reverse Engineer Pedagogy to give students practical and employment-ready learning along with the opportunity to implement end-to-end MLOps Lifecycle. The program offers deployment-based learning across BFSI, Retail, Healthcare, Manufacturing, Supply Chain, and Automobile industries.

Ready to transform your career?

Program Highlights

AI and ML Solutions

Gain AI and ML knowledge to select optimal models for business needs and solve industry problems.

AI Networking Forum

Learn, interact & collaborate with AI experts working at Fortune 50 companies.

ML Production Pipeline

Build end-to-end machine learning systems, implement the ML lifecycle, and deploy them to production.

Career Accelerator

Join our career accelerator program for job preparation, including mock interviews, resume prep and certification training.

Program Overview

Building a strong foundation of knowledge and skills is essential before diving into the
more intricate aspects of AI. To develop a comprehensive understanding of AI, you will be
trained on the following prerequisites as a learner in the field of AI.



Introduction to Al & Nature of Intelligence


Algorithms and Data Structure

◦ Basic Concepts and algorithms
◦ Algorithmic Complexity
◦ Data Structures


Mathematics of Machine Learning

◦ Linear Algebra
◦ Multivariate Calculus


Exploratory Data Analysis & Feature Engineering

◦ Data Exploration and preprocessing
◦ Feature Engineering

MODULE 3 & 4

Statistics and Probability for Data Scientists & Python Programming Language


Introduction to Machine Learning

◦ Learning from Data
◦ Supervised Machine Learning
◦ Neural networks and Introduction to Deep Learning

Who is this program for?

IT Professionals, Software Engineers, Data and Business analysts who want to unlock new opportunities for career growth and chart a cutting-edge career path.

Recent science, technology, engineering, and mathematics (STEM) graduates and academics who want to enter the private sector and scale the positive impact of evolving technologies.

Program Prerequisites

  • A bachelor’s degree or higher in STEM fields
  • Some experience with Python, SQL, Statistics, and Calculus
  • Minimum of 2 Years of Software Engineering/Data Science Experience

*Eligibility-based exemption for the two months Foundational Course.

Get Certified

Upon completing this course, you will be awarded with a certificate of completion from

Why Enrol Now

This is the only course that offers unique ‘Reverse Engineer Pedagogy ’ that enables you to learn
hands-on skills in AI, ML, Deep Learning, Language, Vision, MLOps, ML Pipelines. It offers an
opportunity to work on Industry problems across various domains and industries.

Our Unique Pedagogy

Introduce a problem.

Reverse engineer the learning process of AI and ML by focussing on the application of the problem.

Introduce the nearest available dataset available for that

Explore the nature of data associated with the problem and explain methods of Exploratory Data Analysis.

Introduce the high-level approach to the solution.

Impart the intuition to solve a problem, design thinking, and various methods to solve an AI problem.

Introduce the algorithm(s) that
can solve the problem.

Introduce the intuition of the algorithm. Showcase a tool or library that can solve the problem.

Deep dive into the algorithm.

The mathematical formulation and Hyperparameters of the algorithm.

Design and deployment of the solution.

Learn to Operationalize ML and deploy models in production environment on Amazon AWS SageMaker, Kubeflow, Azure ML Studio, and GCP.

Industry Project Case Study

  • Network Intrusion Detection
  • Weather Forecasting
  • Image Classification
  • Predictive Text Generation
  • Customer Lifetime Modelling
  • Churn Prediction
  • Speech Synthesis
  • Named Entity Extraction
  • Car Navigation
  • Diagnosis

*As an integral component of the course, learners will be assigned individual case studies to analyze and work on. The case study distribution will be randomized to ensure an equitable and unbiased learning experience for all participants.

Tools to Master

Learning outcomes of the certification program

The program is focused on deployments, applications & understanding of various techniques of AI across various verticals and horizontals of an enterprise. The student gets to deep dive into building ML systems, pipelines & solutions using various forms of AI methods – Natural Language Processing, Computer Vision, with different kinds of data (labeled, unlabeled, IoT Device data), etc.

Program Director

Dr. Sid J Reddy

Principal Scientist at Google,
Ex-Principal Data Scientist at Amazon Alexa Seattle, Ex-Principal Applied Scientist at Microsoft

He Designed, developed, and contributed to dozens of AI systems used in production in a wide array of use cases and industry verticals (Health, Business Intelligence, Life Sciences, Legal Enterprise, and E-commerce).

He developed text mining infrastructures from scratch at two technology startups, at the Mayo Clinic, and at Northwestern University, where he led a team of scientists, engineers, and annotators. His research is featured in over 110+ publications and submitted patents in AI (machine learning, deep learning, information retrieval, reinforcement learning, dialog systems, information extraction, summarization, and question answering).

Industry experts from Fortune 50 companies

Chirag Ahuja

Sr. Applied Scientist | OCI – Oracle Cloud Infrastructure

Bhaskarjit Sarmah

Data Scientist at BlackRock

Subhodeep Dey

Lead Data Scientist, JIO
Ex-Data Scientist, UnitedHealth Group

Shreyans Mehta

Chief Data Scientist, ApnaKlub,
Ex-Data Scientist, BlackRock

Give us a call or write to us anytime, we endeavour to answer all enquiries within 24 hours on business days.

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