Post Graduate Certificate Programme in Data Science for Climate and Health

Data serves as a critical tool in addressing global challenges like climate change and healthcare disparities. According to a research by Market Research Future (MRFR), the healthcare big data analytics market alone is projected to grow from USD 215.71 Billion in 2023 to USD 794.08 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 24.26% during the forecast period (2023 - 2030). Fuelled by several intrinsic and extrinsic factors including increasing access to the internet and data itself, acceleration of digital transformation efforts around the world, and increasing investments in advancing social issues- there is an opportunity to shape and develop 3.5 million data professionals globally, focused on social impact areas in the next 10 years

 In collaboration with data.org, BITS Pilani WILP has designed a unique 11-month PG Programme in Data Science for Climate and Health. Designed to equip working professionals in the health and climate domain with essential data skills, this programme enables organizations in these domains to leverage data effectively to fulfil their missions. With this programme, you can become a data scientist for global change.

 

50% / 75% scholarship will be awarded to working professionals at the discretion of the institute, and subject to meeting the eligibility. For more details, visit ‘Fee and Scholarship' section below.

Option to pay fees using easy EMI with 0% interest

Duration

Duration

11 Months

Programme Fee

Programme Fee

INR 2,45,000

Admission

Admission

Open

Scholarship

Scholarship

50%/ 75% scholarship for eligible applicants

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Programme Highlights

  1. 11-month Post Graduate certificate programme for working professionals aspiring to create a global impact in the domain of climate and health.
  2. 50% / 75% scholarship will be awarded to working professionals who meet the scholarship eligibility criteria.
  3. The programme uses extensive digital content including expert lecture videos, and engaging digital learning material.
  4. Access to BITS Pilani instructors through technology-enabled contact classes which can be accessed from anywhere, Q&A support, and discussion forums.
  5. Program offers 4 segments, each with one or two modules, to create an awareness, through application of the tools and techniques to real problems in climate change, health and their intersection
  6. An optional refresher module at the program's outset to cover topics such as Introduction to Python programming, Data Types, Program constructs, Numpy, Pandas, Matplotlib, and Debugging Python programs.
  7. Techniques segment comprises of 4 modules offering a comprehensive understanding of key data analysis methods.
  8. Applications segment includes two modules that explores the practical application of these methods in Climate Change and Health laying the groundwork for capstone project
  9. An 8-week project addressing a real-life problem in Climate Change, Health, or their intersection.
  10. The programme uses a Continuous Evaluation System that assesses the learners over convenient and regular intervals.
  11. Participants who successfully complete the programme will become members of an elite & global community of BITS Pilani Alumni.
  12. Option to pay fees using an easy EMI with 0% interest and 0 down payment

Programme Curriculum

The 11-month Post Graduate Programme in Data Science for Climate and Health consists of 6 Courses and a Capstone Project.

Regression

Regression as a type of supervised learning technique where the target attribute is a continuous variable; regression models from theoretical and implementation perspectives. Model selection and performance measures; Issues with regression models such as overfitting and the ways of combatting overfitting like ridge and lasso regression; Interpretability/explicability of the models;

Feature Engineering

Feature Engineering as a step to develop and improve performance of Machine Learning models; Data wrangling techniques that help transforming the raw data to an appropriate form for learning algorithms; Data preprocessing techniques such as normalization, discretization, feature subset selection etc. and dimension reduction techniques such as PCA. Different ways of visualizing the data such as Box plots, Contour plots, Heat maps etc

Classification

Classification is a type of supervised learning techniques where the target attribute takes discrete values; Three types of techniques to solve classification problems – discriminant function, generative, and probabilistic discriminative approaches. Algorithmic perspective of popular classification algorithms - k-NN, Naïve Bayes, Decision Tree, Logistic Regression and SVM. Implementation details of these models along with tuning of parameters. Ensemble methods, bagging, boosting, Random Forest and eXtreme Gradient Boosting. Interpretability/explicability of the models

Unsupervised Learning and Association Rule Mining

The course focuses on finding natural groups or clusters that are present in the data. The course will cover lustering algorithms like K-means, Hierarchical & DBSCAN algorithms, Hidden Markov Models for time series prediction, and market basket analysis to generate the interesting rules from a transactional database.

Data Science for Climate Change

Evolution (long-term climate data time series analysis, simple statistical models etc), current extent (spatial visualization, new data collection techniques such as AWS, satellite based platforms and citizen science based data collection, its assimilation) and future projections (regional climate modelling, climate data downscaling, and bias correction using deep learning and other DS tools) of the climate change at global, regional and local scales; Solution concepts such as GHG inventory, mitigation pathways (from simple statistical models to complex integrated Assessment model – IAMs); theories and practical case-studies; social aspects of data collection, selection and use (biases, distortions, and blindspots, and the role governance and ethics)

Data Science for Health

Need for ML in healthcare, Real world applications and examples; Different data types available from healthcare systems (EMR, population, surveillance etc.); Handling of unstructured data (medical images, clinical text, Biomedical signals); ML techniques for health data; Deployment of AI models in clinical workflows; Challenges in clinical ML - data challenges, interpretability; Ethical and regulatory issues for AI in healthcare - bias, fairness, privacy and security considerations

Real life problems encompassing a typical data science pipeline obtained from organizations/third party vendors; Jointly mentored by the industry experts and faculty; Comparative study of the relevant techniques covered in the VII-50 course; Presenting the results in the required format; Fortnightly review of progress of the project.

Mode of Learning

The Mode of Learning used in this programme is called - Work Integrated Learning. Internationally, Work Integrated Learning (WIL) is defined as "An educational approach involving three parties - the student, educational institution, and employer organization(s) - consisting of authentic work-focused experiences as an intentional component of the curriculum. Students learn through active engagement in purposeful work tasks, which enable the integration of theory with meaningful practice that is relevant to the students' discipline of study and/or professional development*.

An education model can be considered as WIL if and only if:

  1. The programs are designed and developed by the institute in collaboration with industry.
  2. Work-focused experiences form an active part of the curriculum.
  3. The program structure, pedagogy and assessment enable integration of theory-with relevant practice.

The innovative Work Integrated Learning Programs (WILP) of BITS Pilani are quite aligned with the above definition and requirements. The programs are designed in collaboration with its industry partners, subject matter experts from industry and academia that enable the students to remain relevant in their chosen profession, grow in their career and retain the habit of lifelong learning. The continued availability of workplace related experiences along with the weekly instruction sessions promote integration of theory with practice. Case studies, simulation exercises, labs and projects further strengthen this integration.

The WILP of BITS Pilani is comparable to its campus-based programs in terms of structure, rigor, instruction, labs, assessment, faculty profile and learning support. The pervasive adoption of technology in all its academic processes makes the same high-quality education of BITS Pilani available to the aspirants at scale with the required flexibility. 

Key Benefits of BITS Pilani WILP

1)Students can pursue the programme without any career break and along with the job.

2) The programme curriculum is highly relevant to the climate and health domains.

3) Effective use of technology to deliver a range of learning interventions such as faculty contact sessions, asynchronous learning, remote, virtual and cloud labs, learner support, peer to peer collaboration etc.

4) Comprehensive examinations will be scheduled at the end of Course 3 (for courses 1,2, 3) and Course 6 (for courses 4, 5,6) and are conducted mostly at designated examination centres distributed across the country (for details, click here)

5) Learners can access engaging learning material which includes recorded lectures from BITS Pilani faculty members, course handouts and recorded lab content where applicable.

Mode Of Examination

Mode of Examinations applicable for students admitted in Batch starting in April / May 2024:

Comprehensive examinations will be conducted for each Course in the programme. These exams are typically conducted at the end of Course 3 (for Courses 1, 2, 3) and  Course 6 (for Courses 4, 5, 6) before starting the Capstone Project. These examinations are mostly scheduled on Friday, Saturday or Sunday. Students need to appear in person for taking the examinations at the institution’s designated examination centres as per the examination schedule, Instructions, rules and guidelines announced before every examination. 

Students can take their examination at any of our 23 designated examination centres in India at the following locations:

South Zone: Bangalore, Chennai, Hyderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram and Coimbatore. 

North Zone: Delhi NCR, Jaipur, Chandigarh, Lucknow and Pilani. 

West Zone: Mumbai, Pune, Goa, Ahmedabad, Indore and Nagpur.

East Zone: Kolkata, Bhubaneshwar, Guwahati and Jamshedpur.

In addition to these locations, the Institution also has a designated examination centre in Dubai.

In addition to the comprehensive examinations for each course, there will also be Quizzes/Assignments conducted online on the Learning Management System (LMS) as per the course plan in which the students need to participate.

Eligibility Criteria

To participate, the candidate must possess one of the following qualifications: Working professionals from relevant disciplines, holding a four-year B.Tech. degree or equivalent, or M.Sc. degree in mathematics/statistics.

Fee & Scholarship

The following fees schedule is applicable for the Post Graduate Programme in Data Science for Climate and Health

Programme Fees : INR 2,45,000 (including GST)

Fee Payment Schedule:

  • Block Amount: INR 25,000 (payable within 7 days of receipt of provisional Admission Offer Letter
  • Remainder Programme Fee: INR 2,20,000 (payable within 15 days of receipt of Final Admission Offer Letter)

For details on No-cost EMI option with 0% interest, Click Here

Scholarship will be awarded to the following two categories of applicants subject to the institution's norms. 

Category -1 : 50% scholarship* will be awarded to working professionals who meet programme eligibility criteria and are selected based on their existing work profile and an interview conducted by the Institute’s designated officials. The interview will be conducted online after one week of the submission of the application, and supporting documents. For details on how to apply, click here

Category - 2: 75% scholarship* will be awarded to those employed in NGOs operating in the space of Climate and Health who meet programme eligibility criteria and are selected based on their existing work profile and an interview conducted by the Institute’s designated officials. The interview will be conducted online after one week of the submission of the application, and supporting documents. For details on how to apply, click here.

*A limited number of scholarships are available, and will be awarded at the discretion of the institute, and subject to meeting the above mentioned criteria for both the categories. 

Refund: Participants may cancel their admission within the first 14 days from the start of the cohort, i.e. Programme Start date (launch of Course 1). He/ She will be eligible to get a full refund of programme fee paid, minus the bank processing charges, and applicable taxes (the taxes won’t be refunded). Refund will be processed within a maximum of 45 working days. The participant will be required to fill in a refund form that will be made available by the Admission Cell. Important: For every course in the program institute will recommend textbooks, students would need to procure these textbooks on their own.

 

How to Apply

  • Click here to visit the BITS Pilani Online Application Center. Create your login at the Application Center by entering your unique Email id and create a password of your choice.
  • Fill up the online application form
  • Detail out your objectives behind applying for this programme (not more than 500 words)
  • Description of your work profile (not more than 500 words)
  • Institute will evaluate your application form & supporting documents, and if eligible will schedule an online interview with designated officials.
  • Applicants selected will receive a provisional admission offer letter, along with scholarship details if applicable. 

Upon receiving the Provisional Admission Offer Letter, along with scholarship (if any), you will need to pay a block amount of INR 25,000 within 7 days using the Online Application Center. 

  • Upload the required documents
  • Scanned copy of Passport size photograph.
  • Scanned copy of self-attested Graduation degree certificate and marksheets.
  • Proof of ID (Govt. issued ID such as Driving License, Passport, Aadhaar, Voter ID, etc.)
  • Proof of employment, such as Work Experience Certification from current employer.

Pay the balance amount depending on the allocated scholarship (if any), within two weeks of paying the block amount or the batch start date, whichever is earlier

Student Speak

FAQs

To participate, the candidate must possess one of the following qualifications: Working professionals from relevant disciplines, holding a four-year B.Tech. degree or equivalent, or M.Sc. degree in mathematics/statistics.

This certification programme runs for 11-months with approximately 440 expected learning hours.

The program comprises 7 courses (including a project) and a TBD number of credit units. WILP foresees that some admitted students might have completed the PG certificate program in Artificial Intelligence and Machine Learning or higher-level programs in Data Science or AIML. These programs fulfill the requirements for admission to the PG certificate program in Data Science for Climate and Health, with significant overlap in course content. Graduates from these programs may be considered for admission under a provisional policy allowing advanced standing. This policy involves the following 4 courses (and the 8 credit units corresponding to these courses) be waived from their graduation requirement:

Course No.-

 
Course Title Units
Regression 2
Feature Engineering 1
Classification 3
Deep Learning and Artificial Neural Networks 2

Successful completion of the certificate programme would require completion of all the courses with a minimum C- grade in each course.

Upon successful completion of the programme, participants will receive a degree certificate from BITS Pilani.

The Degree of Master of Technology in Software Systems

The programme is designed for working professionals, and participants are not required to travel to a BITS campus. However, certain programme offer Campus Immersion Modules such as workshops or seminars, which are highly recommended but not mandatory.

Yes. The qualification will provide you the prestigious BITS Pilani Alumni status, through which you will become member of an elite & global community of BITS Pilani Alumni.

This 11-month  Post Graduate Certificate Programme in Data Science for Climate and Health is crafted to assist working professionals in two major ways:

  • Getting a grip on Data Science by learning various tools and techniques for analyzing data.
  • Applying these skills to address actual challenges in climate change, health issues, and where these fields intersect.