- Data Science - Context and Definition
- Actionable Insight
- Data - Basic Concepts
- CRISP-DM : A Process Framework based on Scientific Method
- Multidisciplinary Knowledge and Computing Technologies
- Key Takeaways
- Next Steps
If you have absolutely no idea what Data Science is and are looking for a very quick non-technical introduction to Data Science , this course will help you get started on fundamental concepts underlying Data Science.
If you are an experienced Data Science professional, attending this course will give you some idea of how to explain your profession to an absolute lay person.
There are lots of very good technical and programming focused courses available on Data Science in Udemy and elsewhere.
This short course will lay a firm foundation for better understanding and appreciation of what is being taught in advanced Data Science courses.
Gopinath Ramakrishnan , a Data Science & Machine Learning enthusiast has worked extensively on collection and analysis of data from software projects to create performance baselines for continuous improvement in several IT services and product organizations. He also developed software reliability and defect prediction models.
Gopinath conducted several training and consulting sessions on Software Metrics and Models which helped in establishing data-driven project management culture in the organizations he worked for .
Gopinath is also an Agile Coach & Trainer and has provided several training and consulting services in this area also.
He has more than 20 years of experience in IT industry. His expertise is backed up by a strong background and hands-on work in diverse areas like software development, project management, customer support, R & D , technical sales and academic research.
Gopinath is a Professional Member of ACM (Association for Computing Machinery) . He has earned Advanced Communicator – Bronze certification from Toastmasters International.
Educational Qualifications : Ph.D & M.Tech (Mech.), IIT Madras, India
Skill set - Statistics, Machine Learning , Deep Learning, Python, R, Agile Methodologies