Program Objective:
The Post Graduate Program in Data Science with ML and AI (Formerly known as PGP in Business Analytics) aims at equipping students with the tools, techniques and skills to enable a seamless absorption into the domain of Analytics and grow into the roles of Data Scientists. Praxis thus focuses on offering its students a comprehensive analytics experience, a deep-dive that ensures extensive coverage, rigor and hands-on lab-work in the following:
Technology Skills:an understanding of a wide range of tools like Python, R, Spark, Excel, SQL, SAS, Hadoop, MongoDB (NOSQL), Amazon AWS (EMR / EC2), QlikView and Tableau that are commonly used to extract, analyse and visualize data.
1.Statistical Modeling and Analytical Skills: knowledge of statistics, data mining, machine learning and deep learning techniques and the ability to create predictive models
2.Applying analytics to business situations: a fair understanding of business functions like marketing, finance, operations and the application of Analytics in verticals like BFSI, retail, telecom, Healthcare etc.
3.Communication and Visualization Skills: the ability to tell an effective story.
Methodology
Business Analytics & Data Science lie at the intersection of three key disciplines, namely Statistics & Machine Learning, Programming and the targeted Business Domain and the 9 month program at Praxis is designed to address all three in significant depth.
The backbone of analytics is the theory of statistics in general and machine learning in particular and these two key areas are offered as two different subjects. Both these subjects have ‘lab’ sessions where the students use Python to apply the theory. In parallel, students are also taught SAS and R for the implementation of key concepts from statistics and machine learning.
Students are introduced to the principles of Big Data using Hadoop/ Spark and Python. Students learn how to migrate and port machine learning applications from their laptops to the Amazon AWS platform so as to understand how to leverage the power of large clusters.
Students are exposed to a set of near real world projects obtained from a variety of sources. Faculty use data available from Kaggle competitions to create assignments and student solutions are benchmarked against global leaderboards.
Case studies borrowed from the Business Management program of Praxis give students a basic grounding in the principles of horizontal domains like finance and marketing and in vertical areas like retail and telecom so that they can relate to the “business end” of business analytics.
Finally, a comprehensive, practice-based course on business communication enhances the story-boarding skills of the students and prepares them to ‘tell the story’ of the business problem and the consequent analytics solution – a skill all data scientists need.
Students may click here to access the manual of policies.
The program is divided into three trimesters of three months each comprise classroom training on campus addressing the three pillars of Analytics:
1. Techniques
2.Tools & Technology
3.Business Insights
Eligibility
Who is the Business Analytics & Data Science Program for?
The Praxis program is targeted at candidates who are serious about carving a career in analytics for themselves – and are willing to commit a full year to learning. These are candidates who wish to see themselves grow as successful Data Scientists.
Admission Process
1.Application - Students can apply online from Praxis website – www.praxis.ac.in
2.Tests Accepted - Praxis Admission Test (PAT)/CAT / XAT / GMAT / GRE (Last three year scores are accepted). Praxis reserves the right to conduct the Praxis AdmissionTest (PAT) in order to assess the candidate’s suitability.
3.Selection Process - Short list by assessment test score and profile. Shortlisted candidates appear for an interview with a panel comprising representatives from Praxis and the industry.
4.Interview Centres - Bangalore, Bhubaneshwar, Chennai, Guwahati, Hyderabad, Kolkata, Mumbai, New Delhi, Patna*
5.Assessment Dates- Fall Intake – January to May 2020
6.Spring Intake – September to December 2019
7.Course Commencement - Fall intake – July 2020
8.Spring intake – January 2020
