“A breakthrough in Machine Learning would be worth ten Microsofts." - Bill Gates

Machine Learning is the construction of algorithms that learn from and respond to large datasets faster and make effective predictions. It instructs computers to find patterns in data without being explicitly programmed and provides ‘high-value predictions that can guide better decisions and smart actions in real time without human intervention’. While the concept of Machine Learning has been around for a long time, the ability to automatically apply complex mathematical calculations to big data – ceaselessly and quickly – is gaining strength only in recent times.

Today, Machine Learning is the #1 skill in-demand globally amongst programmers, with a 3,977% growth since 2015. Today's demand for expertise in Machine Learning far exceeds the supply, and this imbalance will become more severe over the coming decade.

S P JAIN OFFERS A 6-MONTH FULL-TIME PROFESSIONAL PROGRAM SOLELY DEDICATED TO MACHINE LEARNING. The program offers professional training, allowing students to sense how Emerging Technologies, like Machine Learning, are enabling new business models, and reshaping the way the economy and businesses operate.

 

PLEASE NOTE: THIS PROGRAM IS NOT ACCREDITED BY TEQSA, ASQA OR ANY REGULATORY BODY IN INDIA OR OVERSEAS.

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Machine Learning Facts:
  • Machine Learning’s potential to deliver real-time optimisation across industries is just starting to evolve, and is set to accelerate and offer greater opportunities over the next three years
  • The spending on Machine Learning and AI is set to reach $47 billion by 2020 globally
  • Research indicates the creation of 140,000- 190,000 Deep Learning talent positions over the next few years
  • Over 2 million – 4 million projected demand for business translators over the next decade
Developed in collaboration with industry experts and leaders, the program will equip you to: 
  • Uncover new market opportunities and be at the forefront of technology innovation.
  • Access and analyse structures and unstructured data at a level that has been until now, unimaginable
  • Help businesses achieve new levels of intelligence and efficiency by designing intelligent business processes
  • Asses customer data, actions, transactions and experiences to improve customer service, loyalty and retention.

From cutting-edge programming languages like Python, R, and Apache Spark to specialist topics like Trees & Networks, Support Vector Machines, Deep Learning, and Hidden Markov -- over a period of 6 months, the program takes you deep into practically every aspect of Machine Learning. And, not simply from a theoretical perspective, but through a practical, real-world approach. In addition to acquiring a focused education surrounding topics in the field, the program enables you to define and streamline your domain expertise, build professional skillsets, network with industry leaders and experts and apply technologies to uncover new market opportunities.

We offer an intellectually stimulating classroom environment steered by front-runners in business and academia who nurture participants to initiate, develop and launch ideas. These include industry experts, business leaders, visionary thinkers, innovators, strategists, researchers, entrepreneurs, pioneers and executives who have been the key enablers of innovation at leading multinational organisations. 

In the last six years of our short but checkered thirteen-year-old history, we have been ranked by three of the world's top four business school rankings -- Forbes, Financial Times and the Economist. In each of these rankings, we are the youngest school featured -- an accomplishment we attribute to our unique and innovative approach to business education that has resulted in higher employment outcomes for our students. Today, our graduates work at some of the world's top companies like McKinsey & Co., Bain & Company, Google, Facebook, Apple, Amazon, the Boston Consulting Group, Unilever, Johnson and Johnson and the World Economic Forum.

 

 
The program aims to bridge the gap between theoretical knowledge and practical application of Machine Learning. The program duration includes: 
  • 16 weeks of classroom training & lab work
  • 8 weeks of industry internship

CLASSROOM LEARNING & EXPOSURE: The program features 16 weeks of classroom learning and lab work designed to instil rigour, knowledge and real-world understanding of Machine Learning. Set within the traditional definitions of a classroom, participants are exposed to specialist topics in Machine Learning, discussions and debates with peers (drawn from varied industries and work backgrounds), and interactions with industry experts and leaders who bring with them up-to-the-minute insights and experience of creating Machine Learning applications. These include both world-class professors and practitioners who have predominantly worked in the technology space. 

This is followed by an 8-week industry internship that helps translate the knowledge gained in the first part of the program into an actual real-world execution, the outcome of which would contribute substantially to the achievement level of the learner in the program.

APPLICATION-BASED LEARNING IN THE LABThe ‘Cloud Lab’ presents a virtual and physical lab environment for students to apply some of the concepts they learn in class and develop real-time solutions for business challenges. Using sophisticated software, hardware and other latest tools, students work together to execute their assignments, gain deep insights on the subject, and build a strong portfolio of real-world strategies. Panels of industry experts, drawn from several fields, support and mentor students throughout the course of the program. 

The program kick-starts with an overview of the discipline's most common techniques, tools and application. As you progress in the program, the focus shifts to more specialist topics like Trees and Networks, Support Vector Machines, Deep Learning, Model Selection, Recommendation Systems, Hidden Markov and POMDP Models. Here’s a sampling of the topics that the program will cover:

  • The Basic Setup
  • Regression
  • Classification
  • Clustering
  • Dimensionality Reduction
  • Trees and Networks
  • Neural Networks
  • Support Vector Machines
  • Deep Learning
  • Optimisation
  • Regularisation
  • Resampling
  • Model Selection
  • Association Rule Learning
  • Recommendation Systems
  • Network Models
  • Ensemble Methods
  • Detecting Anomalies and Outliers
  • Hidden Markov and POMDP Models
  • Evolutionary Learning
On completion of the program, students will have developed a world-class skillset in their selected technology domain that provides “Employability Enhancing” skills and capabilities. It is expected that the program will substantially increase the earning potential and compensation benchmarks of the student. Candidates can expect to be hired in positions such as:
  • Machine Learning Specialist
  • Data Science Researcher
  • Data Engineer 
Salaries for these profiles are on an average 95% higher than Software Programmer jobs with a similar background and experience.

SP Jain offers an intellectually stimulating classroom environment steered by front-runners in business and academia who nurture participants to initiate, develop and launch ideas. These include industry experts, business leaders, visionary thinkers, innovators, strategists, researchers, entrepreneurs, pioneers and executives who have been educated at institutes such as Stanford, Columbia, Lancaster, IIT, IIM and BITS-Pilani. Many of them have the unique distinction of being the key enablers of technology innovation at leading multinational organisations.

PROGRAM DIRECTOR - Dr. Debashis Guha

Dr. Debashis Guha has more than two decades of experience in data analytics and machine learning, with an emphasis on economic and financial applications. He is the founder and CEO of a Bangalore based data analytics company, and has consulted for governments, central banks, multinational corporations and financial institutions across the world, and has taught in both USA and India. Dr. Guha is a graduate of IIT Kharagpur, and has a PhD from Columbia University in New York. 

FACULTY PROFILES

MAHENDRA MEHTA
PhD – Electrical (IIT Bombay)
Area of Expertise: R

SATISH PATIL
PhD (University of Minnesota); B.Tech; EEP – Business Analytics &
Intelligence (IIM Bangalore)
Areas of Expertise: Machine Learning, Statistics

AMITABHA SINHA
MS (IIT, Illinois, Chicago, US); B.Tech (IIT Delhi),
EPGP (IIM Bangalore)
Areas of Expertise: Machine Learning, Deep Learning in Data Science

ANAND CHITIPOTHU
M.Tech (IISc); B.E
Area of Expertise: Python

ANUPAM MONDAL
PhD Scholar (NTU Singapore); M.Tech; B.Tech (Jadavpur University)
Area of Expertise: Text Mining

DIPANKAR DAS
PhD; B.E
Area of Expertise: NLP

NIKHIL GUJAR
M.L (UniSA); MBA (NITIE); B.Tech (IIT Bombay)
Areas of Expertise: Data Structure, Algorithm

NARASIMHA KARUMANCHI
MS (IIT Bombay)
Areas of Expertise: Data Structure & Algorithm (Python)

RAMMOHAN MULAAPUDI
MS (IIT Bombay)
Areas of Expertise: Distributed Computing, HADOOP, Apache SPARK

RAGHAVSHYAM (SHAAM) RAMAMURTHY
MBA (Syracuse University)
Area of Expertise: Visualization

SRIVATSA SRINATH
MBA (IIM Bangalore); MS (Penn State University);
B.Tech (IIT Madras)
Area of Expertise: Machine Learning

SIDHARTH RAMACHANDRAN
MBA (IIM Kozhikode); B.Tech (IIT Roorkee)
Areas of Expertise: SPARK, HADOOP

SUNEEL SHARMA
M.Sc.-Tech. (BITS, Pilani); Entrepreneurship Educators Course; (IIM-Bangalore, Stanford University); Ph.D. (University of Rajasthan); Postgraduate Certificate in Academic Practice (CAP) (Lancaster University, UK)
Area of Expertise: Big Data Visualization

SUNIL D LAKDAWALA
PhD (Yale University); M.Sc (IIT Bombay)
Area of Expertise: Data Warehousing

YOGESH PARTE
PhD – Applied Mathematics (France); M.Sc (IISc Bangalore);
B.E (Pune University)
Areas of Expertise: Mathematics, Machine Learning, Time Series

SANDEEP KHURANA
Fellow Program in Management (PhD) in Information Systems; PGP (Management); B. Tech. (Electronics); B. Sc.
Currently pursuing a PGP in Management from the Indian School of Business

PRAKASH JHAWAR
Manager - Analytics at IndiaFirst Life Insurance
Masters in Mathematics & Computing, IIT Guwahati
machine_learning_brochure
 

To apply for the Professional Technology Program in Machine Learning, you must* have: 

  • An undergraduate/postgraduate degree in a discipline with a strong quantitative component 
  • Two or more years of relevant work experience

PROFILE-BASED SHORTLISTING:

To create an enriching and challenging learning environment, we invite students with exceptional professional backgrounds (five or more years of relevant experience) to apply for the program. As such, the application process may be fast-tracked for such exceptionally qualified candidates. 

 
Click here to submit your application.

Appear for further evaluation, comprising a written aptitude test (Test of reasoning, numerical ability, English comprehension) and a personal interview (Aptitude + Evaluation Fee: INR 3,000). 

The total tuition fees for the program is INR 5,00,000 (plus GST).
 
 

Admissions are open to our December 2017 intake. 

Gain the insights and practical know-how needed to leverage Machine Learning tools and applications to solve complex business problem. Start at SP Jain. 

 Apply now

The SP Jain Machine Learning is also offered in Part-Time format.
Click Here to know more.