Certification
Guide to DeepSeek AI
Guide to DeepSeek AI training program guides learners through a clear, repeatable, step-by-step workflow for working with DeepSeek models, focusing on practical execution rather than simple chat-based interaction. Learners are taught how to define objectives, select appropriate DeepSeek models for different tasks, prepare inputs, refine outputs through iteration, and validate results for real-world use. The training emphasizes that model choice directly affects clarity, consistency, and reliability, while building transferable skills that are not tied to a single platform. Strong attention is given to quality control and responsible use, including recognizing model limitations, avoiding over-reliance on generated content, and being mindful of data sensitivity, licensing, and attribution.
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 Daniel Koh
Dr. Daniel Koh is a data scientist, educator, and entrepreneur with over 18 years of experience applying data science, analytics, and AI to solve complex real-world problems. He specializes in bridging rigorous analytical methods with business and policy decision-making, particularly in contexts where clarity, accountability, and ethical considerations matter.
Dr. Koh is actively involved in education and professional training, where he designs and delivers structured programs in data science, AI, cybersecurity analytics, and digital literacy. His work emphasizes not only technical competence, but also critical thinking, governance, and responsible use of data and AI in organizations and society.
Beyond teaching, Dr. Koh contributes as a thought leader and practitioner, advising institutions and organizations on data strategy, analytics capability building, and evidence-based decision-making. He is known for translating complex technical concepts into accessible frameworks that support executives, policymakers, and learners across diverse backgrounds.
