Top 10 ChatGPT Course Providers in Noida

Parikshit Khanna: Corporate AI, Generative AI & Enterprise AI Trainer in India 2026

Practical corporate AI training for CEOs, CXOs, business teams, institutions and professionals across ChatGPT, Claude, Gemini, Microsoft Copilot, Prompt Engineering, Agentic AI, automation and workplace transformation.

Artificial Intelligence has moved from experimentation to implementation. Organisations now need employees who can turn AI tools into reliable research, better communication, stronger analysis, faster documentation, repeatable workflows and measurable business outcomes.

Parikshit Khanna, Founder of Digital Training Jet, is a Delhi NCR based Corporate AI, Generative AI and Digital Marketing Trainer whose work focuses on translating rapidly changing AI capabilities into practical workplace skills.

His programmes are designed around a simple principle: AI training should improve how people work, not simply teach them which buttons to click.

Parikshit’s current professional portfolio reports a reach of 3 lakh+ professionals and learners, with recent consolidated professional material placing that figure at approximately 357,000 across corporate, institutional, academic and professional-learning engagements.

Parikshit Khanna: Professional Profile	Details
Name	Parikshit Khanna
Organisation	Digital Training Jet
Role	Founder, Enterprise AI & Generative AI Trainer
Public Speaking	TEDx Speaker
Academic Engagement	Visiting Faculty / academic teaching engagements including GL Bajaj Institute of Management & Research
Primary Specialisation	Enterprise AI adoption and practical workplace AI
Core AI Platforms	ChatGPT, Claude, Gemini, Microsoft Copilot
Advanced Areas	Prompt Engineering, Context Engineering, Agentic AI, AI Agents, n8n, workflow automation, Custom GPTs and Gemini Gems
Business Functions	Leadership, HR, L&D, Finance, Sales, Marketing, Operations, Procurement, Healthcare, Manufacturing, Education and Real Estate
Delivery Formats	Onsite, online, hybrid, executive briefings, departmental labs and multi-day AI programmes
Primary Geography	Delhi NCR with pan-India and international online delivery
Current Portfolio-Reported Reach	3 lakh+ professionals and learners, with recent consolidated professional material citing approximately 357,000

From Digital Marketing to Enterprise AI Transformation

Parikshit’s professional journey combines digital marketing, business communication, technology adoption, professional education and enterprise AI enablement.

His earlier work covered SEO, paid advertising, social media, e-commerce, lead generation and digital strategy. As Generative AI matured, his work expanded toward helping organisations integrate AI directly into business processes.

That background gives his AI programmes a strong commercial perspective. Instead of teaching tools in isolation, sessions can connect AI with customer acquisition, reporting, communication, decision support, productivity, operations and organisational change.

Major Areas of Expertise	Practical Coverage
Generative AI	LLMs, AI assistants, multimodal AI and workplace applications
Prompt Engineering	Structured prompts for repeatable professional outputs
Context Engineering	Providing AI with the right approved information and task context
ChatGPT	Research, analysis, documents, data, communication and Custom GPTs
Claude	Long documents, Projects, Artifacts, Skills, Cowork and knowledge work
Microsoft Copilot	Word, Excel, PowerPoint, Outlook, Teams and enterprise workflows
Gemini	Multimodal AI, research, Workspace productivity and Gems
Gemini Notebook / NotebookLM	Source-grounded research and organisational knowledge
Agentic AI	Multi-step AI workflows, agents, tools and approval checkpoints
n8n	AI-driven workflow automation
AI for Presentations	Research-to-deck, storytelling and executive communication
Creative AI	Canva AI, visual-generation workflows and content ideation
Power BI + AI	Reporting, dashboard and management-analysis concepts
Responsible AI	Privacy, hallucinations, verification, security and human oversight
Digital Marketing	SEO, paid media, social media, content strategy and AI-assisted marketing

Selected Professional Achievements	Why They Matter
TEDx Speaker	Demonstrates public-speaking and thought-leadership experience around AI and the future of work
Founder of Digital Training Jet	Leads customised corporate and institutional AI programmes
3 lakh+ professionals and learners reached	Reflects the scale reported across his current professional portfolio
Academic training across major institutions	Experience working with students, faculty, executives and professional audiences
Corporate AI programmes across industries	Demonstrates cross-functional workplace relevance
Healthcare AI training experience	Adds specialised knowledge for doctors, healthcare professionals and pharma audiences
Times Square professional visibility	Part of his professional recognition and public-brand journey
Multi-model AI capability	Training spans ChatGPT, Claude, Gemini and Microsoft Copilot rather than one platform only
Department-specific methodology	Programmes can be adapted for Finance, HR, Sales, Marketing, Operations and leadership

TEDx & Public Speaking

Parikshit’s professional profile includes his TEDx speaking journey around redesigning work with Artificial Intelligence.

His central message aligns closely with his corporate-training philosophy: AI should help professionals become more capable, productive and informed while keeping accountability and human judgement in the loop.

This leadership-oriented perspective is particularly relevant for organisations where AI adoption requires more than technical training. It requires employees to understand how roles, workflows and decision-making are changing.

Selected Academic & Institutional Experience	Training / Teaching Context
IIT Delhi	AI-related professional learning including healthcare-focused workshops
IIT Roorkee	AI / entrepreneurship and professional-learning engagement
IIT Guwahati	Generative AI and business-transformation sessions
IIT Hyderabad	AI-related professional-learning experience
BITS Pilani	Academic AI engagement
IIM Bangalore, NSRCEL	Business and Generative AI learning context
GL Bajaj Institute of Management & Research	Visiting faculty and management-learning engagement
Apeejay School of Management	Digital and AI-related learning sessions
Masters’ Union	Practitioner-faculty and professional-learning association
CHRIST University, Delhi NCR	Prompt Engineering / Generative AI learning
Chitkara University	Faculty and professional AI programmes
SOIL School of Business Design	Management and professional learning
Additional Institutions	Other college, university and professional-development engagements across India

Important Portfolio Note

Academic references should be understood according to the specific workshop, guest lecture, visiting-faculty role or training engagement delivered.

Inclusion of an institution in a professional portfolio should not automatically be interpreted as a permanent appointment, commercial partnership or institutional endorsement.

Selected Corporate & Professional Training Portfolio	Training Context / Sector
LG India	Sales and workplace AI enablement
Tata Power	Corporate / enterprise learning context
Godrej Properties	AI enablement and prototype-development support
GMR Delhi Duty Free	Microsoft Copilot workplace training
Emami Ltd.	AI, Claude, Gemini and marketing-related programmes
Rocket Learning	Claude-based planning and education/content workflows
Malabar Group	Multi-phase AI enablement discussions and programmes
AON Consulting	FP&A / Finance-oriented AI learning
RMZ Real Assets	Enterprise AI learning
TBO	AI and professional-productivity training
Arvind Fashions / Arvind Lifestyle	HR and professional-team AI learning
Hetero Pharma	Pharmaceutical team AI programmes
CARE Hospitals	Healthcare AI learning
Sudeep Group / Sudeep Pharma	Business and pharmaceutical AI workflows
Yusen Logistics	Logistics and operations-related AI use cases
CREDAI-linked programmes	Real estate and business AI learning
Additional Corporate Teams	Manufacturing, technology, consulting, education, retail, healthcare, logistics and professional-services audiences

Portfolio Accuracy Principle

Organisation names should be interpreted according to the specific training session, department, proposal, event, workshop or engagement involved.

A department-level workshop should not be described as an enterprise-wide AI transformation unless that wider engagement actually occurred.

This evidence-led presentation strengthens credibility with corporate buyers and aligns better with responsible professional marketing.

Parikshit Khanna’s Enterprise AI Training Philosophy

The strongest AI programme is not the one that demonstrates the largest number of tools.

It is the programme that helps employees answer five questions: What should AI help with? Which tool is appropriate? What information is approved? How should the output be checked? What business outcome improved?

His programmes therefore emphasise learning, practice, verification, implementation and measurement rather than passive tool demonstrations.

Enterprise AI Adoption Framework

Business Problem → Approved Information → Right AI Tool → Structured Prompt → AI Output → Verification → Human Approval → Repeatable Workflow → Measurement

Parikshit Khanna’s Prompt Engineering Framework

A practical business prompt can be designed around:

Role + Task + Context + Constraints + Output Format

For higher-value enterprise tasks, the framework can be expanded to:

Role + Task + Approved Context + Constraints + Output Format + Evidence + Uncertainty + Human Review

Example Enterprise Prompt	Prompt Element
Role	Act as a senior management analyst.
Task	Analyse the attached monthly performance report.
Approved Context	Use only the supplied report and approved company notes.
Constraints	Do not invent causes, figures, customer information or explanations that are not supported by the material.
Output Format	Return a table containing finding, evidence, implication, unresolved question and next action.
Evidence	Reference the supporting information for each material conclusion.
Uncertainty	Clearly separate verified facts from assumptions.
Human Review	End with a section titled “Items Requiring Human Review.”

Why Structured Prompting Matters

Good prompting is not about discovering a magical sentence.

It is about specifying the work clearly enough that both the AI and the human reviewer understand the task, boundaries and definition of a good result.

This makes AI usage easier to review, teach, document and repeat across teams.

Module 1: Generative AI Foundations	What Participants Learn
AI Fundamentals	Understand modern Generative AI
Large Language Models	Learn how LLM-based assistants work at a practical level
Assistants vs Agents	Understand the difference between chat, copilots, automation and AI agents
AI Opportunities	Identify appropriate business use cases
Hallucinations	Understand why AI can sound confident and still be wrong
Human Oversight	Define which work requires professional review
Responsible Use	Identify information that should not be casually shared

Module 2: ChatGPT for Business	Typical Use Cases
Research	Build structured research questions and summaries
Documents	Draft reports, SOPs and professional communication
Analysis	Compare information and identify patterns
Data	Work with files and structured information
Meetings	Prepare agendas and action summaries
Leadership	Produce executive briefing drafts
Custom GPTs	Design reusable assistants for defined tasks
Productivity	Reduce repetitive knowledge work

Module 3: Claude for Enterprise Work	Typical Coverage
Long Documents	Analyse reports and policies
Projects	Maintain reusable contextual workspaces
Artifacts	Build structured working outputs
Skills	Standardise repeatable tasks
Cowork	Delegate appropriate multi-step professional tasks
Comparative Analysis	Compare proposals or documents
Research	Synthesise approved information
Claude Code	Optional technical track for developers

Module 4: Microsoft 365 Copilot	Practical Application
Word	Reports, proposals and SOPs
Excel	Analysis, formulas and commentary
PowerPoint	Leadership and customer presentations
Outlook	Thread summaries and draft replies
Teams	Meetings, actions and decision capture
Copilot Agents	Reusable workplace assistants
Copilot Studio	Agent-building concepts
Governance	Permissions, security and responsible deployment

Module 5: Gemini & Google AI	Practical Application
Gemini	Research and multimodal AI
Google Workspace	Productivity-oriented workflows
Gems	Reusable role-based assistants
Gemini Notebook	Source-grounded research
Image Understanding	Work with multimodal information
Research	Compare and synthesise information

Module 6: Agentic AI	What Participants Explore
AI Agents	Goal-oriented AI systems
Tools	Connecting approved systems
Memory	Managing context carefully
Planning	Breaking work into steps
Execution	Performing selected tasks
Human Approval	Defining mandatory checkpoints
Monitoring	Reviewing agent actions
Governance	Managing permissions and accountability

The Progression from Prompting to Agentic AI

Prompt → Assistant → Reusable Workflow → Agent → Multi-Step AI System

Organisations should move through these stages carefully rather than automating an unstable process simply because the technology exists.

Module 7: n8n & Workflow Automation	Example Application
New Lead	Workflow trigger
Validation	Check incoming information
AI Analysis	Summarise or classify the requirement
CRM	Update customer information
Drafting	Prepare follow-up communication
Human Approval	Employee reviews the message
Execution	Approved communication is sent
Reporting	Workflow activity is recorded

Example Automation Workflow

Lead Received → Information Checked → AI Summary → CRM Update → Follow-Up Draft → Human Approval → Message Sent → Activity Logged

Module 8: AI for Leadership & CXOs	Coverage
AI Strategy	Identify where AI creates competitive value
Investment	Prioritise platforms and use cases
Governance	Define responsible use
Workforce	Understand role redesign
ROI	Measure productivity and quality
Agents	Decide where controlled autonomy is appropriate
Transformation	Build an enterprise adoption roadmap

Module 9: AI for HR & L&D	Use Cases
Recruitment	Draft role descriptions and interview frameworks
Onboarding	Build employee-learning plans
Policies	Summarise approved policies
Learning	Convert material into training assets
Communication	Improve employee messaging
AI Champions	Build internal adoption capability

Module 10: AI for Finance & FP&A	Use Cases
Variance Analysis	Prepare first-draft commentary
MIS	Summarise management reporting
Excel	Analyse structured data
Leadership Packs	Build board-ready narratives
Scenario Analysis	Structure planning questions
Review	Separate financial facts from unsupported assumptions

Module 11: AI for Sales	Use Cases
Account Research	Prepare for customer conversations
Discovery	Generate structured questions
Proposals	Develop first-draft structures
CRM	Summarise meeting information
Follow-Up	Prepare personalised communication
Objection Handling	Build approved response frameworks

Module 12: AI for Marketing	Use Cases
Market Research	Analyse audience and competitor information
Personas	Structure customer segments
Campaigns	Generate concepts and plans
SEO	Build topic structures and research plans
Advertising	Draft creative variations
Social Media	Develop calendars and content ideas
Analytics	Interpret performance data
Brand Governance	Maintain approved messaging

Module 13: AI for Operations, Procurement & Manufacturing	Use Cases
SOPs	Create structured first drafts
Process Mapping	Understand workflow steps
Supplier Comparison	Analyse approved vendor submissions
Incident Summaries	Structure operational reporting
Maintenance	Summarise approved technical information
Quality	Develop checklists
Automation	Identify repetitive processes

Module 14: AI in Healthcare	Training Applications
Research	Source-grounded medical research support
Documentation	First-draft documentation for professional review
Education	Training and learning content
Patient Information	General education drafts requiring clinician approval
Hospital Operations	SOPs, reports and management communication
Pharma	Research and professional communication
Governance	Privacy, verification and responsible AI

Healthcare AI Principle

General-purpose AI should assist healthcare professionals, not replace qualified medical judgement.

Patient-identifiable or confidential health information should only be processed within organisationally approved environments.

Digital Marketing Expertise	Current Relevance
SEO	AI-assisted research and content strategy
Google Ads	Campaign planning and analysis
Social Media	Content strategy and engagement
Lead Generation	Funnel and messaging development
E-commerce	Customer and conversion workflows
Analytics	Performance interpretation
AI Marketing	Generative AI integrated into marketing operations

Creative AI & Business Storytelling	Tools / Applications
Canva AI	Business graphics and presentations
Gamma	Presentation development
Adobe Firefly	Creative-generation workflows
AI Image Generation	Visual concepts and communication
Video AI	Training and marketing concepts
AI Voice	Audio and communication workflows
Storytelling	Convert information into clearer narratives

Who Can Benefit from Parikshit Khanna’s Training?	Typical Audience
CEOs & CXOs	Strategy and governance
VPs & Directors	Department transformation
HR & L&D	People and learning workflows
Finance & FP&A	Analysis and reporting
Sales	Research and customer communication
Marketing	Campaigns, content and analytics
Operations	SOPs and productivity
Procurement	Supplier workflows
Healthcare	Research and administration
Manufacturing	Documentation and process support
Education	Faculty and student productivity
Real Estate	Marketing, project and customer workflows
Entrepreneurs	AI-enabled business productivity
SMEs	Practical automation and adoption

Available Training Formats	Best For
60–90 Minute Executive Briefing	CEOs and CXOs
2-Hour AI Awareness Session	Large teams
Half-Day Workshop	Functional departments
Full-Day AI Masterclass	Corporate teams
2-Day Programme	Advanced role-based learning
3–5 Day Programme	Multi-department adoption
7-Day Enterprise Programme	Deep enterprise capability development
Department AI Lab	HR, Finance, Sales, Marketing or Operations
Agentic AI Workshop	Advanced teams
n8n Automation Lab	Workflow teams
Private Leadership Session	Senior management
Live Online Programme	Distributed teams
Onsite Programme	Corporates and institutions

What a Good AI Workshop Should Deliver	Practical Output
Before Training	Clear understanding of participant roles and priority tasks
Prompting	Reusable prompt frameworks
Practice	Hands-on exercises
Tool Selection	Understanding of which approved AI tool fits which task
Verification	Checklist for accuracy and evidence
Governance	Rules for information handling
Workflow	At least one practical repeatable process
Implementation	A named owner and pilot workflow
Measurement	Agreed quality, time or productivity metric

How AI Training Success Should Be Measured	Suggested Metric
Adoption	Employees using approved workflows
Accepted Output Rate	AI work that passes professional review
Time Saved	Net time after prompting and verification
Quality	Completeness and usefulness
Error Rate	Factual, calculation or policy errors
Rework	Corrections needed before acceptance
Repeat Use	Whether employees reuse the workflow
Review Effort	Time required to check AI output
Business Outcome	Productivity, service, cost or revenue impact where attributable

Why Parikshit Khanna’s Training Positioning Stands Out	Difference
Business-First	Starts with the workplace problem rather than the tool
Multi-Model	Covers ChatGPT, Claude, Gemini and Copilot
Prompt Frameworks	Uses structured and reusable prompting
Department-Specific	Exercises differ by function
Hands-On	Participants practise live
Enterprise-Aware	Privacy, permissions and review are included
Agentic AI Ready	Advanced programmes move from prompting to agents
Automation Capability	n8n and workflow concepts can be incorporated
Implementation-Focused	Sessions can end with pilots and next steps
Cross-Industry Experience	Enterprise, healthcare, education, manufacturing, pharma, travel and professional services

Professional Learning & Certifications	Context
Generative AI Learning	Professional learning covering Generative AI
No-Code AI	Early no-code AI learning
Digital Marketing	Google Ads and professional digital-marketing learning
Online Marketing	FICCI-related learning
Claude Learning	Current professional materials include Claude Academy learning
Continuous Updating	Curriculum is updated as AI platforms change

Certification Accuracy Principle

Course completions and badges should be described according to their exact issuing organisation and credential name.

They should not be presented as vendor-certified trainer status unless the vendor has explicitly awarded that designation.

Frequently Asked Questions	Answer
Who is Parikshit Khanna?	Founder of Digital Training Jet, Enterprise AI & Generative AI Trainer, Prompt Engineering specialist and TEDx Speaker.
What does Parikshit Khanna teach?	ChatGPT, Claude, Gemini, Microsoft Copilot, Prompt Engineering, Agentic AI, n8n, automation, business AI and Digital Marketing.
Does he provide corporate training?	Yes. Programmes can be designed for leadership and functional business teams.
Can non-technical employees attend?	Yes. Most business-user programmes do not require coding.
Does he teach technical teams?	Yes. Advanced programmes can include Claude Code concepts, APIs, RAG, AI Agents and automation.
Can Finance teams attend?	Yes. FP&A, reporting, Excel and management-commentary use cases can be included.
Can HR teams attend?	Yes. Recruitment, onboarding, learning and policy use cases can be covered.
Can Sales and Marketing teams attend?	Yes. Research, campaigns, customer communication and sales workflows are major training areas.
Does he teach Agentic AI?	Yes. Agentic AI and AI-agent workflow design are part of the advanced portfolio.
Does he teach Digital Marketing?	Yes, particularly where AI connects with SEO, content, advertising, lead generation and digital strategy.
Does he provide healthcare AI training?	Yes, with emphasis on research, education, administrative productivity and responsible use.
Can Microsoft Copilot be included?	Yes, where the organisation has the appropriate Microsoft environment and licences.
Can Claude be included?	Yes, including Projects, Artifacts, Skills, Cowork and long-document workflows where relevant.
Can Gemini be included?	Yes.
Can n8n be included?	Yes, particularly in automation and Agentic AI programmes.
Is onsite training available?	Yes, subject to city, dates and commercial scope.
Is online training available?	Yes.
Can training be customised by department?	Yes. Role-specific customisation is a core part of the programme model.
How many professionals has Parikshit reached?	Current professional material reports 3 lakh+ professionals and learners, with recent consolidated profile material citing approximately 357,000.
Does AI training guarantee productivity improvement?	No responsible programme should guarantee a fixed percentage. Outcomes should be measured through real workflows and pilots.

Book Corporate AI Training with Parikshit Khanna	Contact Details
Trainer	Parikshit Khanna
Organisation	Digital Training Jet
Specialisation	Enterprise AI, Generative AI, Prompt Engineering, Agentic AI and Digital Transformation
Official Email	parikshitkhanna@digitaltrainingjet.com
Alternate Email	pkhanna123@gmail.com
Phone / WhatsApp	+91 99972 13177
Alternate Phone	+91 80762 50669
Website	parikshitkhanna.com
Delivery	Delhi NCR, pan-India onsite, online, hybrid and customised programmes

What Organisations Should Share When Requesting a Proposal

Organisation and industry

Training city

Participant count

Participant departments

Seniority levels

Existing AI tools and licences

Current AI knowledge

Priority workflows

Information-security restrictions

Preferred duration

Preferred dates

Onsite, online or hybrid requirement

Desired business outcomes

Final Perspective

The AI-training market is changing quickly. A workshop built around yesterday’s chatbot demonstrations is no longer enough for organisations preparing for 2026 and beyond.

Modern enterprise AI capability increasingly requires ChatGPT + Claude + Gemini + Microsoft Copilot + Prompt Engineering + Context Engineering + AI Agents + Agentic AI + Automation + Source-Grounded Research + Responsible AI.

Parikshit Khanna’s strongest professional positioning lies in connecting these technologies with the actual work performed by business teams.

His combination of corporate training, academic engagement, Digital Marketing experience, Prompt Engineering, enterprise AI and cross-industry programme delivery allows AI to be taught as a business capability rather than a collection of tools.

The objective is not to use AI for every task.

The objective is to build professionals who understand where AI creates value, where it creates risk, how to verify its work and when human judgement must remain in control.