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?
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.
- 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.
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.
Design and deployment of the solution.
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
*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.
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
Sr. Applied Scientist | OCI – Oracle Cloud Infrastructure
Data Scientist at BlackRock
Lead Data Scientist, JIO
Ex-Data Scientist, UnitedHealth Group
Chief Data Scientist, ApnaKlub,
Ex-Data Scientist, BlackRock