M.S. in Biotechnology Innovation and Computation Curriculum
The Core Curriculum (84 units)
Our core curriculum is based on four main phases of innovation development which include opportunity identification, opportunity development, business planning and concludes with business incubation. This process is described below:
Students enter the program by taking courses in sequence that correspond to these four phases. Each course is designed to provide them with the skills necessary to analyze a problem set, evaluate possible solutions, and synthesize this learning into the development of a capstone project that will be developed in segments throughout the program. In addition to these courses, students will take additional courses to supplement their knowledge of specific areas such as Machine Learning, Search Engine, Big Data Analytics, Data Mining, Text Mining, and Cloud Computing, etc.
Phase One: Opportunity Identification
11-651 Artificial Intelligence & Future Markets (12 units)
In this first core course, students learn to analyze and synthesize emerging technological trends to understand how these trends can help shape or disrupt existing markets. Students will identify an emerging trend or opportunities that they would like to work on. Students will form teams and propose their solution to a particular firm (through one of the program advisors). Upon approval, students will learn how to develop requirements analysis and convert that into feature definition.
Phase Two: Opportunity Development
11-695 Competitive Engineering (12 units)
In the second core course, students learn that customer requirements are often a moving target: they’re influenced by the energence of competitive alternatives (e.g. internal consultants, off-the-shelf software, new technology.) and by the team interaction with others. Students will learn to create a prototype or Minimum Viable Product that best captures the best balance of the customer priorities and feasibility and distinguishing it from competitive alternatives. At the conclusion of the term, teams will compete with each other to determine which team’s product is superior.
Phase Three: Enterprise Planning and Scaling Up
11-654 Enterprise Development (12 units)
In this third core course, students learn how to build a start-up by developing a business model and strategy for the product. Students will learn about customer development, customer validation, proposal, product branding, and marketing for their product. The course will require students to spend the time to validate their start-up business model with potential customers and adapt to critical feedback and revise their respective value propositions accordingly. Students learn to balance technical product development with customer requirements, business strategy and budget constraints. By understanding customer discovery and validation concepts, students will learn how to pivot, modify their original concepts to meet market demands.
Phase Four: Forming Companies and Growing Founders
11-699 Program Capstone (36 units)
The final term will integrate all of the acquired learning in the program towards the development of a formal software product. The effort involved in the capstone project is quite intense and will consist of approximately four months of full-time work for each student. The expected deliverables (features to be developed, business plan, technical documentation, etc.) must be agreed to by the course instructor at the outset of the course. The capstone can meet the development of an industry-sponsored software project or a software product intended for entrepreneurial startup.
Students are expected to showcase their business and software products and elicit feedback from academics, industry professionals, investors, and business executives. This phase also acts as an incubation period for start-ups. The capstone should complete by the end of the spring term.
Students are required to take and complete 192 units:
1) The Core Courses (72 units – must be taken in sequence):
- 02-651 – New Technologies and Future Market (12 units)
- 11-695 – Competitive Engineering (12 units)
- 02-654 – Biotechnology Enterprise Development (12 units)
- 11-691 – Capstone Project (36 units)
2) The Knowledge Area Courses (84 units):
- 10-600 – Math for Machine Learning (12 units)
- 11-601 – Coding Boot Camp (12 units)
- 10-601 – Machine Learning (12 units)
- 11-675 – Big Data Systems in Practice (12 units)
- 02-750 – Automation of Research/Machine Learning Robotics (12 units)
- 02-604 – Fundamentals of Bioinformatics (12 units)
Students can select one out of the following three courses:
- 02-613 – Advanced Algorithm & Data Structure (12 units)
- 15-513 – Introduction to Computer Systems (12 units) Or
- 11-611 – Natural Language Processing (12 units)
3) Electives (36 units):
A minimum of 36 units of LTI, CBD or SCS courses must be taken.
Examples include but are not limited to:
- 02-710 – Computational Genomics (12 units)
- 02-712 – Computational Methods for Biological Modeling (12 units)
- 02-730 – Cell and Systems Modeling (12 units)
- 11-411 – Natural Language Processing (12 units)
- 11-676 – Big Data Analytics (12 units)
- 11-642 – Search Engines (12 units)
- 15-619 – Cloud Computing (12 units)
- 17-637 – Web Application Development (12 units)
- 15-615 – Database Applications (12 units)
- 15-640 – Distributed Systems (12 units)
- 15-645 – Database Systems
- 11-741 – Information Retrieval (12 units)
- 15-826 – Multi-Media Web Mining (12 units)
- 11-661 – Languages and Statistics (12 units)
- 11-683 – Mathematical Foundations for Data Science (12 units)
- 10-605 – Machine Learning With Large Data Sets (12 units)
- 11-755 – Machine Learning Using Signal Processing (12 units)
- 11-643 – Machine Learning in Text Mining (12 units)