www.bits-pilani.ac.in/wilp M.Sc. BUSINESS ANALYTICS Work Integrated Learning Programmes
M.Sc. BUSINESS ANALYTICS The globalisation of the Indian economy and related deregulation has led to the phenomenon of global labor arbitrage, wherein jobs move to nations with skilled workforce and low cost base. This phenomenon has triggered a rapid growth and development of the Business Analytics (BA) industry. In addition the liberalisation and opening up of the Indian economy to foreign investments has facilitated the development of new and innovative approaches to business. All of these actions have resulted in an increased demand for qualified and skilled Business Analytics professionals. The five-semester M.Sc. Business Analytics offered by BITS Pilani intends to bridge this gap, and enables the participant to develop specialised skills via a carefully chosen set of electives. The programme is suited to the learning requirements of professionals in the Business Analytics industry, as well as professionals working in other industries/ functions such as the IT, BFSI, Marketing, etc., who have a keen interest in Business Analytics and looking for a career transition to BA role. PROGRAMME HIGHLIGHTS Highly qualified and experienced faculty from BITS Pilani as well as industry experts will deliver the lectures Exposure to state-of the-art data analysis/ visualisation tools such as R, SAS, and Tableau Practitioner oriented insights (from industry experts) to help develop solutions to real world problems using cutting edge analytical techniques Our unique Work Integrated Learning Program (WILP) approach combines class room learning with experiential components and enables participants to immediately apply their learning to the workplace and thereby enhance their career growth PROGRAMME OBJECTIVES To prepare working professionals to take on challenging roles in the nascent Business Analytics industry (particularly in the context of globalisation) To train the students in the latest developments in the area of Business Analytics (across various industry verticals) To equip them with a good mix of theoretical and cutting edge practical skills so they can be immediately effective and productive on the job
LEARNING OUTCOMES Upon completion of this programme, the participants will be able to effectively apply the following principles and concepts: Apply statistical data analysis and other decision science techniques to optimally solve real world business problems Objectively analyse alternatives using quantitative techniques Apply cutting edge tools and technologies to analyse Big Data Develop appropriate algorithms using machine learning techniques to solve business problems Be able to effectively communicate the results of the analysis using appropriate data visualisation techniques Demonstrate the ability to work effectively in cross functional teams ELIGIBILITY The candidate should have passed Mathematics as a subject in 10+2 and at an undergraduate level. Primarily candidates with a B.Sc./M.Sc./B.E./MCA/MBA or equivalent with minimum 60% aggregate marks will be eligible to apply. However students with other qualifications (such as B.Com (Hons), etc.) may apply provided they have done a basic mathematics course (such as Business Statistics) at the undergraduate level (in addition to 10 + 2 level). The candidates should have completed minimum 12 months post-qualification full-time relevant work experience Employer consent, with suitable mentor availability, is also required. FEE STRUCTURE The following fees schedule is applicable for candidates seeking new admission during the academic year 2016-17 Application Fees (one time) : INR 1,500 Admission Fees (one time) : INR 15,000 Semester Fees (per semester) : INR 40,750
SEMESTER-WISE PROGRAMME STRUCTURE Participants need to take 7 foundation courses (mandatory), 6 area core courses (mandatory) and may choose any 4 elective courses depending on their background and desired specialisation. In addition, during the final semester of the program, participants are required to complete a capstone project that is relevant to their work environment and enables them to integrate their learning across the entire program. First Year First Semester Marketing Management Information Systems Models and Applications in Operational Research Introduction to Statistical Methods First Year Second Semester Financial Management Business Data Mining Supply Chain Management Introduction to Data Science Second Year First Semester Advanced Statistical Methods Big Data Analytics Predictive Analytics Optimisation Methods for Analytics Second Year Second Semester Analytics for Competitive Advantage Elective 1 Elective 2 Elective 3 Third Year First Semester Elective 4 Project Pool of Electives Advanced Financial Modeling Data Visualization Financial Risk Analytics HR Analytics Investment Banking Analytics Marketing Analytics Marketing Models Retail Analytics Supply Chain Analytics Real-time Analytics Text Analytics HOW TO APPLY Please note that in order to apply to a WILP programme, the candidate must be currently employed in the relevant professional field. Carefully read through the following steps to understand the application process: 1. Choose the programme, and apply using the Online Application Form through the WILP website. 2. After you complete and submit the Online Application Form, you will be taken to a new webpage where you will see an online payment link to pay the Application Fee of INR 1,500/-. You can pay the Application Fee of INR 1,500/- through Netbanking/ Debit Card/ Credit Card. You may also pay using Demand Draft/ Bank Challan.
The Application Fee may either be paid immediately upon submitting the Online Application Form, or later by retrieving your form using Retrieve Your Form link under the Quick Links section of the website. 3. The new webpage will also allow you to download a PDF of the complete Application Form. Using the Download Your Form' link, save the PDF copy of your Application Form to your computer. 4. Take a printout of the downloaded Application Form and note down the Application Form Number that appears on the top-right corner of the first page. This Application Form Number should be referred in all future correspondence with BITS Pilani. 5. In the printout of the downloaded Application Form, you will notice on page no. 3 a section called the Employer Consent Form. Complete the Employer Consent Form. This form needs to be signed and stamped by your organisation s HR or any other authorised signatory of the company. 6. Further on page no. 4 of the printed Application Form is a section called the Mentor Consent Form. You must find a senior person from your employing organisation who is willing to become your Mentor. The Mentor Consent Form needs to be signed by the Mentor. 7. Further on page no. 5 of the downloaded Application Form, is a Checklist of Enclosures/ Attachments. Make photocopies of the documents mentioned in this Checklist Get these photocopies attested by your organisation s HR, or a Gazetted Officer On the Checklist, please tick against all the documents that you have enclosed along with your Application Form 8. The printed Application Form, along with duly filled Mentor Consent Form, Employer Consent Form, Checklist of Enclosures, and attested photocopies of supporting documents should be put together and couriered to: Admissions Cell Work Integrated Learning Programmes Birla Institute of Technology & Science, Pilani Vidya Vihar Campus, Pilani Rajasthan 333 031 (India) 9. Upon receipt of your Application Form and all other enclosures, the Admissions Cell will scrutinise them for completeness, accuracy and eligibility. 10. Once received by us, you will be able to track the status of your Application Form using the Application Status Tracker. CURRICULUM DETAILS Foundation courses Business Data Mining Financial Management Introduction to Statistical Methods Management Information Systems Marketing Models and Applications in Operations Research Supply Chain Management Foundation courses help build a strong foundation in the underlying theory and practice relating to Business Analytics. They are designed to give participants a solid background in Statistical/ Quantitative methods and related Data Analysis techniques. In addition, they enable the participants to develop the necessary understanding across relevant business disciplines so as to enable them to work effectively in cross functional teams and take quick decisions that require the ability to integrate knowledge across business functions.
Area Core courses Advanced Statistical Methods Analytics for Competitive Advantage Big Data Analytics Introduction to Data Science Optimisation Methods for Analytics Predictive Analytics Area core courses provide the necessary base of knowledge in Business Analytics and Data Sciences. These set of courses equip the participant with the core set of Data Sciences, Data Mining, Big Data Analytics, and other relevant skills that is essential for extracting meaningful information from the multitude of data that is collected by business and organisations across the globe. These courses will equip the participants with the tools and techniques to make better business decisions and thereby build a sustainable competitive advantage. Elective courses Advanced Financial Modeling Data Visualisation Financial Risk Analytics HR Analytics Investment Banking Analytics Marketing Analytics Marketing Models Retail Analytics Supply Chain Analytics Real-time Analytics Text Analytics Electives provide specialised knowledge relating to sub-areas and specialisations within Business Analytics. The Data Visualisation elective helps participants to learn how to effectively present analytical findings in a visual manner so that it is easy to make decisions and identify new patterns. Finance electives such as Advanced Financial Modeling, Financial Risk Analytics, and Investment Banking Analytics enable the participants to learn how to leverage business analytics techniques to deliver a competitive business advantage in diverse areas such as fraud detection, trading analytics, etc. Similarly each of the other courses in this group allows the participant to master a specialised body of knowledge that is relevant for managers to harness the power of Business Analytics within the context of their business function and industry.