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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | University of Texas, AustinGreat Learning |
The fees for course Post Graduate Program Artificial Intelligence for Leaders is -
| Head | Amount |
| Programe fees | Rs. 1,95,000 + GST |
| EMI | Rs. 4,719/ month |
The Syllabus
- Understand the basics of AI and its rapid growth
- Explore practical applications and limitations of AI in business
- Engage in the step-by-step process of developing an AI project
- Evaluate ROI, threats & opportunities
- Develop a POC outline, evaluate solutions, and assess market potential
- Create a roadmap for product development and expansion
- Understand data objects and visual metrics for data interpretation
- Explore Data Visualization and manipulation
- Learn Machine Learning fundamentals and Regression techniques
- Delve into Logistic Regression and evaluate classification models
- Assess different performance measures—precision and recall
- Engage in case study sessions with experts to apply concepts
- Gain foundational knowledge on Neural Networks
- Explore techniques for optimizing Neural Networks
- Dive into Decision Trees and learn about Pruning techniques
- Delve into Ensemble Techniques and evaluate classification models
- Understand ensemble techniques as a powerful tool in Machine Learning
- Solidify understanding of these concepts using case studies
- Gain expertise in K-Means clustering, scaling, and visual analysis
- Learn content-based and collaborative filtering
- Understand similarity measures, and explore hybrid systems
- Understand the real-world applications of clustering and reinforce knowledge
- Develop practical skills in applying clustering and recommendation systems
- Understand various compositions in AI teams and the roles of individuals
- Learn to build cross-functional AI teams and manage portfolios of the projects.
- Understand NLP fundamentals and methodologies for problem-solving
- Learn techniques for text extraction and web scraping in NLP
- Engage in the practical process of building NLP models
- Explore the basics of Computer Vision (CV) and its problem types
- Delve into the workings of Convolutional Neural Networks in CV
- Apply concepts through case studies and gain insights from experts
Generative AI: What, Why and So What for AI Leader
- Learn the intricacies of developing impactful GenAI use cases from industry experts.
- Understand how to assemble an adept team, navigate data complexities, and consider infrastructure and cost implications.
- Delve into constraints, feasibility factors, and strategies for successful use case development and adoption.
AI For Business Values
- Explore the synergy between data and AI for informed decisions, streamlined processes, and personalized experiences.
- Dive into the industry implications of AI, emphasizing leaders' roles in responsible implementation.
AI Use Cases
- Discover impactful AI use cases across diverse industries curated by experienced mentors.
- Prioritize business impact and witness AI's efficacy in addressing real-world challenges.
- Gain firsthand insights into implemented solutions and tangible benefits.
Building AI Teams
- Unlock effective AI team structures, roles, and hiring strategies.
- Seamlessly integrate data science, employ communication tools, and motivate your team.
- Discover tech-powered solutions to build, manage, and unleash your AI powerhouse.
Strategic MLOps
- Identify business wins and challenges with Machine Learning (ML).
- Evaluate solutions and apply MLOps strategies.
- Delve into key topics like MLOps demystified, effective ML operationalization, navigating DevOps vs MLOps, and overcoming implementation challenges.
Responsible AI
- Explore ethically designed and secure AI systems for success, trust-building, and risk mitigation.
- Gain insights into key principles, industry best practices, and practical implementation strategies.
- Learn from real-world case studies and expert guidance to responsibly navigate the future of AI, ensuring progress and innovation.
- AI Essentials
- Generative AI
- AI in Practice
Instructors
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