Hari Thapliyaal

Dr. Hari Thapliyal is a seasoned professional and prolific blogger with a multifaceted background that spans the realms of Data Science, Project Management, and Advait-Vedanta Philosophy. Holding a Doctorate in AI/NLP from SSBM (Geneva, Switzerland), Hari has earned Master’s degrees in Computers, Business Management, Data Science, and Economics, reflecting his dedication to continuous learning and a diverse skill set.

With over three decades of experience in management and leadership, Hari has proven expertise in training, consulting, and coaching within the technology sector. His extensive 16+ years in all phases of software product development are complemented by a decade-long focus on course design, training, coaching, and consulting in Project Management.

In the dynamic field of Data Science, Hari stands out with more than three years of hands-on experience in software development, training course development, training, and mentoring professionals. His areas of specialization include Data Science, AI, Computer Vision, NLP, complex machine learning algorithms, statistical modeling, pattern identification, and extraction of valuable insights.

Hari’s professional journey showcases his diverse experience in planning and executing multiple types of projects. He excels in driving stakeholders to identify and resolve business problems, consistently delivering excellent results. Beyond the professional sphere, Hari finds solace in long meditation, often seeking secluded places or immersing himself in the embrace of nature.

Ek Kendra for Data Science

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Welcome to dasarpAI — a unique space where Data (of various languages) meets Sanskrit (mother of languages), Project management meets Philosophy, and Machine Learning meets Mindfulness.

I’m Dr. Hari Thapliyaal, the creator of https://dasarpai.com, with 1000+ articles covering AI, Data Science, Project Management, Sanskrit Mantras, and Vedanta.

My Philosophy Behind This Blog

More than just a space for teaching and helping others, this blog serves as my platform for self-expression. The thousands of articles spanning multiple categories are my way of communicating with the world—and reminding myself of how far I’ve come and what remains to be explored.

This is the place to learn everything about Data Science, Data Engineering, Data Analytics, EDA, AI, Machine Learning, Deep Learning, LLM, RAG, GAN, NLP, RL, and much more. The content here is rooted in my three decades of experience across Data Science, Project Management, AI/ML, IT, Software Development, Process Automation, and Business Analytics in diverse domains such as Logistics, BFSI, Healthcare, Education, Staffing, and NGOs.

Over the years, I’ve held roles including Programmer, Architect, Business Analyst, Data Analyst, Product Manager, Project Manager, Program Manager, Delivery Head, Trainer, Coach, Consultant, and Mentor. These varied experiences have given me a deep understanding of how businesses operate—and how technology can help them make better, more timely decisions to maximize stakeholder engagement and drive business growth.

In my view, making business decisions while ignoring critical factors is akin to trying to see the world with one eye. Technology, in itself, is meaningless unless it improves human well-being. We technocrats are not here merely to show off our capabilities; we aim to reduce your pain points, costs, and efforts, ultimately enhancing your overall satisfaction.

Therefore, when developing or adopting new technologies, one must consider the following:

Technical capabilities of the organization
Market competition
Future growth
Current business needs
Project budget
Time to respond
Well-defined business requirements

Data Science Perspectives

In some cases, data is left to “die” in a hard disk in a forgotten storeroom; in others, the data is practically “screaming” for attention in front of us. Often, we hear only the narratives we like. Dying of thirst is a problem, but struggling at the riverbank is an even more common issue for many organizations. The time has come to bring the value of data onto balance sheets—otherwise, maintaining storage with no actionable insights is merely a liability.

On AI Adoption

AI is undoubtedly transformative and continues to reshape businesses. Still, we should first ask whether the current initiative truly needs AI or if a simpler process automation solution would suffice. Due diligence is essential: rather than starting with questions like “How can AI help our business?” or “Which AI tool should we use?”—it’s better to begin by asking, “How can we improve with our existing resources and processes, and what does ‘better’ really mean for us?”

“Better” might mean:

Reducing cost
Improving efficiency
Reducing time to market
Enhancing customer satisfaction
Or any other key metrics important to your team, department, or organization

About Data Science Projects

AI is software, but AI projects are not like typical software projects. They have distinct pipelines and project lifecycles, requiring specialized methodologies and tools. Common objectives might include:

Reducing cost
Reducing development time
Improving quality
Enhancing customer experience
Decreasing turnaround time
Minimizing waste
Preventing last-minute surprises
Ensuring compliance
Boosting brand value
Increasing sales
Or any other metrics critical to your team, department, or organization

The Way I Live in This World

Philosophy connects me to my inner self.
Management connects me to the stakeholders around me.
Technology enables me to create solutions for myself and for those around me.
Before becoming a change agent, it’s vital to first declutter your own mind and the space around you.