Advanced Data Science / Advanced Machine Learning through Python
Advanced Data Science - Machine Learning through Python

48Hours programme

Contact hours: 24 hours

  • Conceptual Learning
  • Hands-on Learning
  • Projects/ Assignments
  • Case studies/ Use cases
For Enrollment
Programme Objectives
The “Advanced Data Science - Machine Learning through Python” programme brings machine learning to life by showcasing real-world use-cases. The programme provides a unique blend of conceptual learning supplemented by hands-on application of popular machine learning techniques, all under the guidance of industry experts with decades of domain knowledge.
Who should go for the Programme?
The “Advanced Data Science - Machine Learning through Python” programme has been designed & developed primarily for analytics and information technology professionals keen to implement machine learning centric solutions to address business problems. In addition, for beginners in the professions of analytics and information technology, the programme imparts the relatively advanced skills in the field of machine learning, thereby providing competitive advantage.

Key Takeaways

  • Envisage & articulate the opportunities for deploying machine learning techniques as problem-solvers in their businesses
  • Develop competency in popular machine learning tools & techniques prevalent in the industry
  • Deliver innovative solutions to business challenges using popular machine learning techniques
  • Formulate & implement strategies for business enhancement and competitive advantage through machine learning

Learning Mode

Are there any Learning Pre-requisites?

The “Advanced Data Science - Machine Learning through Python” programme is essentially of a relatively advanced nature, and hence there are certain learning pre-requisites for the programme. In order to enhance the efficiency & effectiveness of participants’ learning, it is desirable that participants possess basic knowledge of computer programming in any language, preferably in either of C/C++, Java, R or Python. In addition, prior awareness of and/or exposure to probability theory, linear algebra, calculus and basic Statistics would facilitate participants’ learning efficiency. Participants with no prior exposure to Statistics, probability theory, probability distributions, etc, as well as participants who wish to refresh their knowledge of these areas, can rapidly bring themselves up to speed through our specially-designed preparatory programme – the “Essentials of Business Analytics” programme.


Advanced Data Science / Advanced Machine Learning through Python

MEET Our Consultants & Faculty

Dr. Goutam Das

Ph.D. (Economics) IIFT Delhi, M. Tech (Computer Engg) IIT Kharagpur
B.E. (Electronics & Comm) V-NIT Nagpur
30+ Years of experience in IT and Analytics [Business Analytics, Big Data Analytics, AI Machine Learning.
Ex-Cheif Data Scientist at Power Foundation of India...

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Dr. Nidhan "Neal" Choudhuri

Ph.D. (Statistics), Michigan State University.
B. Stats. & M. Stats., Indian Statistical Institute, Calcutta.
Ex-Chief Scientist & Founder, PlanetRisk Inc, Bethesda, US.
20+ years of industry exp. with Morgan Stanley, Barclays Capital etc.

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Mr. Aditya Biswas

B. Tech. (Mechanical) & M. Tech (Industrial Engg. & OR) IIT, Kharagpur.
Ex-Principal Consultant in TCS, Head of IT in Allahabad Bank.
Specialized in Process Optimization, R & D and Management Consulting.
30+ yrs of industry exp.

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Gautam Mukherjee

B.Tech (Electronics & Comm) IIT Kharagpur, M.Tech (Electrical Engg) IIT Madras.
30+ Years of experience in R&D in IT, Telecom. Ex Scientist at DRDO

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Somnath Sinha

B.Tech. (Electrical Engg), IIT Bombay.
PGDM, IIM Calcutta.
20+ yrs with IBM as IT Services Leader, CIO, HR Director &s Director, Integrated Operations.
Partnered with Accenture, IBM, PwC, KPMG, E&Y, etc.
30+ years of industry exp.

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Prof. B. B. Chakrabarti

Ph.D. in Economics, Gold Medalist PGDM, IIM Calcutta.
Gold Medalist - BE, Jadavpur Univ.
20+ yrs as a Renowned Prof of Finance at IIM Calcutta.
24+ years of Industry experience with United Nations, Deustche Bank etc.

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