This course introduces business students to AI-driven analytics techniques that can be applied to business decision-making processes. It covers key AI concepts such as predictive modeling, machine learning algorithms, and data visualization to enable students to make better decisions, predict future trends, and optimize business strategies.
Level- Basic
Prerequisites - Basic understanding of business analytics and data interpretation. No coding knowledge required.
Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Micro Assessment weekly, Final Project-based Assessment.
Job Roles Applicability -Business Analyst, Data Analyst, AI Consultant, Strategy Analyst.
This course introduces AI technologies and their applications in marketing and CRM. Students will explore how AI can be used to personalize marketing strategies, predict customer behavior, and automate customer service. The course focuses on integrating AI into marketing systems to drive customer engagement, retention, and business growth.
Level- Basic
Prerequisites - Basic understanding of marketing and customer relationship management. No coding knowledge required.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments, Final Project-based Assessment.
Job Roles Applicability - Marketing Analyst, CRM Manager, AI Marketing Specialist, Digital Marketing Strategist.
This course focuses on understanding how computer vision technology can be applied in business contexts to enhance decision-making, improve operational efficiency, and drive innovation. Students will learn how AI can process visual data, detect patterns, and automate key business processes like quality control, product analysis, and customer insights.
Level- Basic
Prerequisites - Basic understanding of business analytics, no coding required.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments, Final Project-based Assessment.
Job Roles Applicability - Business Analyst, Product Manager, Operations Manager, Marketing Analyst.
This course focuses on interaction AI, which enhances the ability of businesses to engage with customers and improve internal communication through intelligent conversational agents, chatbots, and virtual assistants. Students will learn how to integrate AI into customer service, marketing, and operations to create innovative business solutions.
Level- Intermediate
Prerequisites - Basic understanding of AI, no coding required.
Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments -Weekly Micro Assessments, Final Project-based Assessment.
Job Roles Applicability - Business Innovation Specialist, Customer Experience Manager, AI Strategist, Product Manager.
This course introduces the core principles of AI project management, specifically tailored for computer vision projects. Students will learn how to manage the lifecycle of AI projects, focusing on defining clear objectives, ensuring proper data collection, selecting the appropriate algorithms, and coordinating with cross-functional teams to deliver successful computer vision solutions. The course will also cover managing timelines, handling stakeholder expectations, and measuring project success in AI-driven environments.
Level -Intermediate
Prerequisites - Basic understanding of AI concepts, no coding knowledge required.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments, Final Project-based Assessment.
Job Roles Applicability - AI Project Manager, Technical Lead, Product Manager, Computer Vision Specialist.
This course covers the best practices for quality assurance (QA) in AI projects, specifically for computer vision applications. Students will learn how to test AI models, ensure the quality of input data, handle edge cases, and validate outcomes to guarantee that computer vision systems meet the desired business requirements and standards. The course also covers methods to deal with issues like overfitting, model bias, and performance issues in real-world applications.
Level-Intermediate
Prerequisites- Basic understanding of AI and computer vision, no coding required.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments, Final Test and Evaluation.
Job Roles Applicability - QA Engineer, AI/Computer Vision QA Specialist, Technical Tester, Data Validation Analyst.
This course focuses on integrating ethics and governance into AI projects. Students will explore frameworks for ethical decision-making, understand regulatory compliance, and learn how to design AI systems responsibly. Topics include mitigating risks, ensuring fairness, transparency, compliance, and accountability, and aligning AI development with societal values and standards.
Level- Intermediate
Prerequisites- Basic understanding of AI concepts.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Case Studies, Final Presentation.
Job Roles Applicability - AI Ethics Specialist, AI Governance Analyst, AI Policy Consultant.
This course focuses on the methods and principles used to assess the value of AI products and systems, both from a technical and business perspective. Students will learn how to evaluate ROI, measure impact, account for costs, and align AI solutions with organisational objectives. The course also explores how to build business cases for AI projects and prioritise features based on their value propositions.
Level- Intermediate
Prerequisites - Basic understanding of AI and Business concepts.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments, Final Valuation Report.
Job Roles Applicability - AI Product Manager, Business Analyst, AI Strategist, AI Consultant, AI Investment Analyst, Investment Banking (AI), Venture Capital, Private Equity.
A key aspect of achieving a working AI is efficient data preparation to meet the planned outcomes. This course explores the entire data lifecycle, focusing on strategies for collection, preparation, integration, and evaluation. Students will gain hands-on experience with data processing techniques, enabling them to understand the pivotal role data plays in AI development.
Level- Intermediate
Prerequisites - Basic understanding of Computer Vision AI or Interaction AI Course.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Case Studies, Final Valuation Report.
Job Roles Applicability - AI Product Manager, AI Strategist, AI Consultant, AI Data Manager, AI Valuation Expert.
This course equips students to tackle custom industry challenges, develop innovative AI projects, or transition research into startups. It spans the full lifecycle of AI development, from conceptualizing solutions to pitching them to stakeholders, focusing on technical proficiency and entrepreneurial acumen.
Level- Intermediate
Prerequisites - Prior three courses at least with one being Computer Vision or Interaction AI.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Weekly Micro Assessments; Full Assessment and Final Presentation in Week
