Apply generative AI, intelligent automation, business intelligence and responsible AI governance to real business decisions and workflows.
This programme develops practical understanding of modern AI systems, prompt and retrieval workflows, automation, analytics, AI agents, governance and business-case development. It is designed for business use: selecting valuable applications, controlling risk and communicating implementation decisions clearly.
Learn to distinguish useful AI applications from weak ones, design controlled workflows, evaluate quality, use business intelligence for decisions and build an implementation roadmap with human oversight, privacy and security controls.
The subject matter can be useful in roles such as:
Role relevance depends on the employer, job level and your wider experience. Completing the programme does not guarantee employment or eligibility for a particular role.
You will progress from AI fundamentals to workflow design, automation, business intelligence, agentic systems and responsible implementation. Each week adds evidence and analysis to a final decision-ready transformation portfolio.
Final applied project: A decision-ready AI transformation portfolio containing prioritised use cases, workflow designs, a BI scorecard, governance controls, business case and 12-month implementation roadmap.
Every week contains three published lessons, two professional resources, a 10-question knowledge assessment and an applied practical submission. Weekly work progressively builds the final programme output.
Understand modern AI categories, where AI creates business value, and the controls required for responsible use.
Applied activity: AI opportunity and risk map.
Connect this week’s work to your final programme deliverable.
Move from casual prompting to reusable, grounded and testable language-model workflows.
Applied activity: Prompt workflow and evaluation pack.
Connect this week’s work to your final programme deliverable.
Combine process redesign, deterministic automation, software integration and AI safely.
Applied activity: AI automation blueprint.
Connect this week’s work to your final programme deliverable.
Turn operational data into reliable metrics, dashboards and decision support.
Applied activity: Executive BI scorecard.
Connect this week’s work to your final programme deliverable.
Design multi-step AI systems that can use tools while remaining observable and controlled.
Applied activity: Agent workflow specification.
Connect this week’s work to your final programme deliverable.
Apply AI across research, operations, commercial, service and knowledge-work contexts.
Applied activity: Functional AI pilot proposal.
Connect this week’s work to your final programme deliverable.
Build practical governance, security and procurement controls for enterprise AI.
Applied activity: Responsible AI governance pack.
Connect this week’s work to your final programme deliverable.
Turn AI pilots into a sequenced, governed and measurable transformation plan.
Applied activity: AI transformation roadmap.
Connect this week’s work to your final programme deliverable.
A growing business wants to use AI across research, customer service and operations. You will compare use cases, design controlled workflows, test quality, define governance and show which initiatives should be piloted, scaled or deferred.
This is a learning scenario for practice and does not promise a live client engagement or employment opportunity.
Beginner-first lessons explain the concepts before you apply them. Weekly assessments test understanding while practical submissions demonstrate professional application.
Start with plain-language explanations of terminology, methods, examples, worked cases and common mistakes.
Use guided resources, templates and professional scenarios to produce practical work each week.
Each weekly 10-question assessment requires 60% to pass and allows up to three attempts.
Finish all eight weeks, approved practical work and the 20-question final assessment, which requires 70% to pass.
The Zariwala & Associates programme credential is issued after the published completion, assessment and payment requirements are met. It is not a university degree, statutory licence, employer endorsement or guarantee of employment.
No specialist experience is assumed. The programme begins with foundational concepts and defines the terminology and methods before requiring application.
The structured pathway is eight weeks with approximately 48 hours of indicative learning. Your learner dashboard shows the published learning sequence, activities and assessment requirements.
A decision-ready AI transformation portfolio containing prioritised use cases, workflow designs, a BI scorecard, governance controls, business case and 12-month implementation roadmap.
Each week includes a 10-question knowledge assessment requiring 60% to pass, with up to three attempts, plus an applied practical submission. After all eight weeks, the 20-question final assessment requires 70% to pass and allows up to three attempts.
After meeting the published completion, assessment and payment requirements, you can access a digitally verifiable credential from your learner dashboard. Each issued credential has its own credential ID and public verification record.
The programme fee is ₹15,000. Any promotional discount is shown before checkout, and the final payable amount is confirmed in the enrolment flow.
Secure Razorpay checkout is available through the enrolment flow. Programme access activates only after successful server-side payment verification.
Programme enrolment fees are non-refundable, subject to any rights that cannot legally be excluded. The enrolment terms are presented before payment.
Review the curriculum, practical work, credential information and enrolment terms. Secure Razorpay checkout is available through the enrolment flow, and programme access activates after successful server-side payment verification.