“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 9-MONTH WEEKEND 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.The program makes use of an advanced Blended Learning model allowing working professionals to build real-world skills and competencies in the subject, without interrupting their full-time careers.
PLEASE NOTE: THIS PROGRAM IS NOT ACCREDITED BY TEQSA, ASQA OR ANY REGULATORY BODY IN INDIA OR OVERSEAS.
Why SP Jain's Machine Learning?
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
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.
Our program, tailored for busy working professionals like you, makes use of a flexible study format that minimises your time away from work and family, and at the same time, helps you develop the skills needed to speed up your momentum at work.
This flexible 'Blended Learning' format offers the most modern way to learn. It combines online home study (over weekdays) with face-to-face and practical learning (over weekends) to create a convenient, technology-enabled learning experience to students.
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 9 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.
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.
- 237 hours of online lessons
- 240 hours of face-to-face lessons over Sundays (including application-based sessions in the Lab)
ONLINE LESSONS: This is the most modern way to learn. Students are given access to a suite of multimedia and interactive learning tools such as blogs, journals, discussion boards, articles and quizzes that help them gain a foundation in Machine Learning, from the convenience of their homes. It is believed that the discipline of online learning enhances learning agility and retention of fundamentals since students learn at a pace that suits them. This section of the program can be completed by the student anytime during the week.
CLASSROOM LEARNING & EXPOSURE: Conducted over weekends and 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.
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
- Dimensionality Reduction
- Trees and Networks
- Neural Networks
- Support Vector Machines
- Deep Learning
- Model Selection
- Association Rule Learning
- Recommendation Systems
- Network Models
- Ensemble Methods
- Detecting Anomalies and Outliers
- Hidden Markov and POMDP Models
- Evolutionary Learning
- Machine Learning Specialist
- Data Science Researcher
- Data Engineer
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 -
PhD – Electrical (IIT Bombay)
Area of Expertise: R
PhD (University of Minnesota); B.Tech; EEP – Business Analytics &
Intelligence (IIM Bangalore)
Areas of Expertise: Machine Learning, Statistics
MS (IIT, Illinois, Chicago, US); B.Tech (IIT Delhi),
EPGP (IIM Bangalore)
Areas of Expertise: Machine Learning, Deep Learning in Data Science
M.Tech (IISc); B.E
Area of Expertise: Python
PhD Scholar (NTU Singapore); M.Tech; B.Tech (Jadavpur University)
Area of Expertise: Text Mining
Area of Expertise: NLP
M.L (UniSA); MBA (NITIE); B.Tech (IIT Bombay)
Areas of Expertise: Data Structure, Algorithm
MS (IIT Bombay)
Areas of Expertise: Data Structure & Algorithm (Python)
MS (IIT Bombay)
Areas of Expertise: Distributed Computing, HADOOP, Apache SPARK
RAGHAVSHYAM (SHAAM) RAMAMURTHY
MBA (Syracuse University)
Area of Expertise: Visualization
MBA (IIM Bangalore); MS (Penn State University);
B.Tech (IIT Madras)
Area of Expertise: Machine Learning
MBA (IIM Kozhikode); B.Tech (IIT Roorkee)
Areas of Expertise: SPARK, HADOOP
M.Sc.-Tech. (BITS, Pilani); Entrepreneurship Educators Course; (IIM-Bangalore, Stanford University);
Area of Expertise: Big Data Visualization
SUNIL D LAKDAWALA
PhD (Yale University); M.Sc (IIT Bombay)
Area of Expertise: Data Warehousing
PhD – Applied Mathematics (France); M.Sc (IISc Bangalore);
B.E (Pune University)
Areas of Expertise: Mathematics, Machine Learning, Time Series
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
Manager - Analytics at IndiaFirst Life Insurance
Masters in Mathematics & Computing, IIT Guwahati
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
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.
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 tuition fee must be paid in the following
- 25% within 7 days of receipt of Offer of Admission
- 75% before 2 weeks of course commencement
|Machine Learning Masterclass Schedule - December'2017 Intake|
|11th November, 2017||Pune||Saturday||The O Hotel, N Main Rd, Ragvilas Society, Koregaon Park, Pune.||11.00 AM to 1.00 PM|
|12th November, 2017||Bangalore||Sunday||Vivanta by Taj – Whitefield, Whitefield Main Rd, ITPB, Whitefield, Bangalore.||4.00 PM to 6.00 PM|
|15th November, 2017||Kolkata||Wednesday||One to One Session - Novotel Hotel and Residences, CF 11 Action Area, 1C New Town, Rajarhat,Kolkata.||6.00 PM to 9.00 PM|
|18th November, 2017||Mumbai||Saturday||SP Jain School of Global Management,1st Floor, Trade Point,Kamala Mills Compound, Lower Parel, Mumbai.||11.00 AM to 1.00 PM|
Admissions are open to our December 2017 intake.
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The SP Jain Machine Learning is also offered in Full-Time format.
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