Certification
Guide to Google's Gemini
Overview:
- A hands-on certification that teaches learners how to use Google’s Gemini through a clear, repeatable, step-by-step workflow.
- The course focuses on practical execution—setting up tasks, structuring prompts, iterating with feedback, validating outputs, and packaging results for real-world use across Google’s ecosystem.
- It is suitable for professionals, educators, analysts, and students who want practical competency with Gemini rather than theory-heavy discussions about generative AI.
In this training, learners follow a structured, step-by-step workflow for using Google’s Gemini effectively and responsibly. The course begins with defining clear objectives and success criteria, then moves into providing precise context and constraints to improve relevance and reduce ambiguity. Learners are taught how to design robust prompt patterns, engage in iterative refinement to improve accuracy, tone, and structure, and strategically guide Gemini toward task-aligned outputs. The training places strong emphasis on quality control, helping learners assess reliability, cross-check critical information, and identify limitations specific to large language models. Finally, learners are guided in converting AI-assisted drafts into professional, submission-ready deliverables while applying responsible-use practices, including data sensitivity awareness, disclosure, and informed judgment on when Gemini should—or should not—be used.
Register
Format: Online
Date: 25 February 2026
Time: 7 - 10pm Singapore time
Fee: US$68
Promotion: Use coupon 20OFF at checkout and enjoy 20% off the course fee
What you Get?
Certification
Obtain a Certificate of Completion accredited by the Association of Data Scientists upon completing the assessment
Step by Step Guide
Get a copy of the step-by-step guide and revisit the steps at your own pace
Trainer
Dr Zulkifli Jalil
Dr. Zulkifli ("Zul") Jalil is a seasoned cybersecurity and artificial intelligence professional with a strong track record spanning industry practice, education, and leadership. Based in Singapore, he combines deep technical expertise with a practical understanding of how emerging technologies are applied in real organisational settings. His work focuses on cybersecurity strategy, AI adoption, digital risk, and the development of future-ready talent.
In addition to his industry roles, Zul is actively involved in education and professional training, where he lectures and mentors learners across cybersecurity, AI, and technology governance domains. He is known for his ability to translate complex technical and security concepts into structured, accessible frameworks that professionals can apply immediately in their work. His teaching and advisory approach emphasises responsible technology use, risk awareness, and alignment between technical decisions and organisational objectives.
Zul also contributes to industry initiatives and partnerships, supporting certification programmes, workforce development, and collaborative projects that bridge academia and industry. Through public engagement and thought leadership, he shares perspectives on digital transformation, professional growth, and the evolving relationship between technology, security, and society. His profile reflects a practitioner-educator who operates comfortably at the intersection of hands-on technical work, strategic thinking, and capacity building.
