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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.

Enrollment

Advanced Data Science / Advanced Machine Learning through Python

MEET Our Consultants & Faculty

Goutam Das

Ph.D. Scholar (Foreign Direct Investment), IIFT Delhi MTech (Computer Engg.), IIT Kharagpur Alumnus of IIM Calcutta & ISI Delhi 25+ yrs of industry exp. across industry verticals

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Dr Nidhan "Neal" Choudhuri

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

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Debjani Bhattacharya

M. Phil, Jadavpur University, B.E. (Electrical Engg.), MN-NIT Allahabad

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Dr. Mousumi Duttaray

Ph.D. (International Economics), Indiana University, USA 18+ years of teaching, research and industry experience in USA with global majors like Barclaycard, AMEX etc.

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Amrita Saha

M.Sc.(Economics) Calcutta University

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Somnath Sinha

B.Tech. (Electrical), IIT Bombay PGDM, IIM Calcutta 30+ yrs. of exp. in global delivery with 2 decades of service with IBM as Service Leader (IT) & CIO Ex-partner of Accenture, KPMG, E&Y, PWC

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Prof. B. B. Chakrabarti

Ph.D. in Economics Gold Medalist -PGDM, IIM Calcutta Gold Medalist - BE, Jadavpur Univ. Fellow Member of the Institute of Cost Accountants of India (ICAI) 40+ yrs of experience in industry/ academic

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Pravin Bhosale

B. E. (Mech. Engg), NIIT PG Certification on Business Analytics, Machine Learning Cert from Stanford Univ. LOMA ALMI Certified Professional 15+ years of experience in consulting on Financial Analytics, Credit Risk Analytics, Operations Research, Business Analytics,

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