AI for Girls: How Parikshit Khanna Is Changing Tech Education in UAE
Updated: 14 hours ago
In a world where technology drives innovation, it’s crucial that everyone, regardless of gender, has the opportunity to lead and succeed. In the UAE, one name is making a powerful impact in this mission: Parikshit Khanna, founder of Digital Training Jet. Through his AI education initiatives, Parikshit is breaking barriers and empowering girls across the Emirates to step into the future of technology with confidence.
Why AI Education for Girls Matters
Despite growing awareness, tech and AI industries still see underrepresentation of women. Early exposure to AI tools, practical skills, and mentorship can help bridge this gap. In the UAE, where digital transformation is a national priority, training young girls and women in AI is not just about inclusion, it's about building the workforce of the future.
What Parikshit Khanna Is Doing Differently
Parikshit’s programs are built to be inclusive, accessible, and hands-on. Here’s how he’s transforming AI learning for girls:
Interactive Bootcamps: Fun, beginner-friendly AI training focused on real-world applications
Women-Centric Cohorts: Special sessions for girls in high school, college, and early careers
Confidence-Building Activities: Public speaking, collaboration projects, and innovation challenges
Mentorship & Career Guidance: Direct access to industry professionals and career coaches
From ChatGPT to image-generation tools and automation workflows, Parikshit introduces learners to AI in a way that’s exciting and empowering.
Success Stories
Case Study: High School Girls in Abu Dhabi
Program: AI Bootcamp for Beginners, led by Digital Training JetOutcome:
Over 100 students learned to use ChatGPT for academics and creativity
5 student-led AI projects showcased at a local tech fair
Parents and teachers praised the confidence boost among participants
Case Study: College Girls in Dubai
Program: Advanced AI Tools for Marketing & Content CreationOutcome:
Students created AI-powered business proposals
Several participants landed internships with UAE startups
Why Schools & Institutions Trust Parikshit Khanna
Decade-long experience in digital transformation and training
Culturally sensitive, education-focused approach
Proven track record with corporates and academic institutions in the UAE
High engagement rates and positive feedback from participants
Join the Movement: Bring AI Training to Your Girls’
School or College
Contact Parikshit Khanna: +91 8076250669
Website: www.parikshitkhanna.com
Let your girls dream big and code bold. With the right AI education, they can lead tomorrow’s tech revolution.
🚀 Empower. Educate. Elevate, With Parikshit Khanna’s AI Training.
Dubai and UAE training guide: practical learning and booking
This guide expands the topic "AI for Girls: How Parikshit Khanna Is Changing Tech Education in UAE" with trainer background, relevant AI workflows and delivery choices. Organisations can use it to prepare a training brief and compare the learning plan with their actual work. The examples below are classroom scenarios, not promises of measured client outcomes.
Parikshit Khanna, founder of Digital Training Jet Pvt. Ltd. and Visiting Faculty at GL Bajaj Institute of Management and Research, teaches AI through the work people already handle. A useful session starts with the participant's role, recurring tasks and existing software. The aim is to turn an unclear request into a usable brief, a reviewed draft or a repeatable workflow. His institutional and corporate engagements provide context for teaching mixed audiences, from individual professionals to department teams.
For a Dubai or UAE organisation, the learning plan can account for English and Arabic communication, multinational teams, customer expectations and approval processes. Participants practise with approved or fictional information rather than exposing confidential records. They learn to specify purpose, audience, source material, constraints and output format, then question the answer. An attractive response still needs evidence, calculation checks and an accountable reviewer.
A practical workshop should leave participants with reusable prompts, a review checklist and one workflow they can explain to a colleague. Before expanding adoption, teams compare a sample of AI-assisted tasks with their current process for preparation time, completeness and correction effort. These observations guide the next session. Tool choice follows the task and available access; enterprise procurement, licences and data permissions should be agreed before sensitive workflows are attempted.
AI training for education, career development and professional learning
Start with a syllabus excerpt, lesson objective and learners' starting level. Draft an activity, short explanation and formative assessment. Map questions to objectives and include reasoning in the answer key. Educators check factual accuracy, reading level and alignment with material actually taught. Measure revisions, curriculum gaps and preparation effort. Producing more questions does not automatically improve learning.
For career development, use a fictional CV and genuine role description. Identify relevant experience, missing evidence and interview practice questions. Suggest clearer wording while preserving qualifications, employers, achievements and actual numerical results. Distinguish a skill gap from a writing problem. The learner reviews all claims before using a draft. A stronger document can communicate experience clearly but cannot guarantee selection, higher salary or a job.
Private sessions can develop research and review habits. Formulate a question, identify sources, request an organised draft and check against originals. Educators practise adapting explanations while retaining facts. Explore permitted ChatGPT, Claude, Gemini or Copilot access according to current availability and organisation permissions. Use fictional student records and approved materials. The outcome is a usable activity or career document, a source-checking checklist and an achievable practice plan, with educators or learners responsible for the result.
AI tools, use cases and review checkpoints
Tool to explore | Practical learning use case | Review checkpoint |
ChatGPT | Draft syllabus-aligned activities or truthful CV and interview practice outlines. | Check source facts, missing information and every proposed commitment. |
Claude | Compare approved documents, summarise long briefs and identify contradictions. | Require source locations; review omitted clauses, assumptions and confidential inputs. |
Microsoft 365 Copilot | Explore drafting and document tasks within permitted Microsoft 365 work content. | Confirm licence, access permissions and the final document with its accountable owner. |
Gemini | Compare draft quality for a permitted research, writing or planning exercise. | Verify factual claims, dates, calculations and the intended audience. |
Canva AI | Turn an approved content brief into a presentation or visual communication concept. | Check brand assets, factual text, accessibility and usage rights before distribution. |
n8n and approved integrations | Connect a tested intake, classification and review workflow after a manual pilot. | Test failures, duplicates, credentials and the approval step before live use. |
Parikshit Khanna: experience to consider when selecting an AI trainer
Experience or milestone | Relevance to your Dubai or UAE programme |
Founder, Digital Training Jet Pvt. Ltd. | Training around a defined business brief, team responsibilities and a practical learning plan. |
Visiting Faculty, GL Bajaj Institute of Management and Research | Structured explanations, guided practice and exercises connecting AI concepts with business decisions. |
TEDxEicher School Faridabad Youth speaker, 2026 | His talk on redesigning work with artificial intelligence explores changes in working methods. |
Corporate engagements including LG Electronics and Siemens | Experience shaping role-specific exercises, communication and approval processes. References do not imply endorsements. |
Institutional engagements including IIT Delhi, IIT Roorkee and IIM Bangalore | Teaching varied audiences and starting levels. Engagement references do not imply institutional certification. |
Experience with Malabar Group and Prasar Bharati | UAE-linked business and public-sector learning context. Confirm the scope and delivery arrangements when booking. |
Author and co-author of two books on technology and AI | Written explanations complement hands-on learning and discussion of practical applications. |
Featured through Topmate in Times Square | A professional visibility milestone, alongside the public consultation and booking profile. |
AI training formats for large companies, small businesses and private learners
Format | Suitable audience | Practical focus |
Leadership briefing | Executives, owners and functional heads | Select a manageable pilot, a named owner and a clear review process. |
Department workshop | Finance, HR, marketing, sales, operations or procurement | Practise recurring tasks, build prompts and agree acceptance criteria. |
Cross-functional corporate programme | Larger organisations and multiple departments | Shared foundations followed by separate team exercises and approval checkpoints. |
SME business session | Small and growing companies | Prioritise maintainable workflows within existing software, access and staff skills. |
Private one-to-one session | Professionals, founders and managers | Work on personal goals, approved sample tasks and implementation questions. |
Follow-up implementation session | Teams that have tried an initial workflow | Review errors, refine prompts and decide which steps need human judgement. |
What to prepare before a training session
Bring two or three recurring tasks, an approved sample input and an example of the output your team considers satisfactory. Explain who creates the work, who checks it and where errors usually occur. A good brief includes participant experience, team size, language needs, existing tools and any restrictions on uploading information. This helps allocate time between foundations, demonstrations and hands-on practice.
A half-day introduction can emphasise prompt design and one department exercise, while a fuller programme can include several functions, peer review and a workflow pilot. These are possible programme shapes, not fixed schedules or packages. Online, on-site and hybrid delivery for Dubai or other UAE locations are subject to availability and an agreed brief. Request a current quotation that specifies preparation, delivery, follow-up, travel where relevant and any software costs. No date, seat, licence or price is confirmed by this article.
Contact Parikshit Khanna for Dubai and UAE AI training
Contact option | Details |
Training enquiry email | parikshitkhanna@digitaltrainingjet.com |
Additional email | pkhanna123@gmail.com |
Phone / WhatsApp | +91 99972 13177 |
Additional phone / WhatsApp | +91 80762 50669 |
Topmate consultation and booking | https://topmate.io/parikshit_khanna |
Share your team size, department, preferred delivery format, existing tools and two or three tasks you want to improve. Parikshit Khanna can discuss a corporate programme, SME workshop or private learning session aligned with that brief. Dates, location, delivery arrangements and commercial terms are confirmed during the booking discussion.
AI assistance and editorial disclosure
This article was updated with AI assistance for research organisation, drafting and formatting, and checked against the sources linked below. Workflow examples are educational, illustrative scenarios rather than measured client results. Tool names explain possible learning applications and do not imply a partnership or endorsement. Features, availability, licences and commercial terms can change; confirm current details and your organisation's data permissions before implementation. Client and institutional references describe training experience without implying endorsement of this article. Training enquiries and bookings are provided by Digital Training Jet. Programme scope and delivery arrangements are confirmed during booking. AI outputs require appropriate human review; productivity, business and search-ranking outcomes are not guaranteed.
