Webinar Startup Teknologi SIMT-ITS x IDS Digital College

Course Description This course is designed to introduce some of the key activities to reach and sustain profitability. The learners will learn the most important rule of entrepreneurship, practice the different kinds of fundraising exercises, and how to develop strategies to retain them. You'll also hear from successful entrepreneurs and venture capitalists, who will talk about what indicators of success they look for when deciding where to invest.   Course Objectives

• Students will have an understanding of what success looks like and how it can be financed.
• Students will be able to pick the financing pathway that's best for their enterprise, use common valuation strategies to set a reasonable price for their company, and negotiate favorable terms.
• Students will be ready for a real roadshow, in which you will get feedback on their pitch deck

  Course Outline

• Introduction Fundraising & Exit Strategy
• Exit Strategy
• Fundraising Exercise
• Investment Cases
• Introduction to New Venture Financing
• Types and Costs of Financing
• Angel Investment
• When, What, Which, Where, and How, on New Venture Financing
• Deal screening
• Valuation and Term Sheet
• Deal Structuring and Negotiation
• Value-added Services

   Text books

•     Thiel, Peter., Masters, Blake., et al.(2014). Zero to One: Notes on Startups, or How to Build the Future. Random House Audio

Course Description This subject of Technology, Data & Analytics aims to enable students to understand the challenge of managing large data sets and to provide them with a skill set to meet this challenge. It combines academic rigour and practical relevance. There is a careful balance of teaching and learning, individual and group work. Case study methodology and class-based discussions are used to strengthen the conceptual, analytical and problem solving skills of the participants in real situations.   Course Objectives

•     Students will discover the fundamental methods and frameworks to help them make sense of their data and use it to make informed business decisions.
• Students can understand the challenge of managing large data sets and provide them with a skill set to meet this challenge.
• Students can demonstrate the analytical skills to interrogate large data sets in a business environment; 
• Students can demonstrate a critical awareness of current issues in Business Analytics
• Students can demonstrate that they have obtained a set of personal development and lifelong learning skills applicable to the international business environment.

  Course Outline Week 1 - Maths & Statistics Primer

•     Introduction to probability theory
•     Basics of probability & statistics
•     Probability models
•     Bayes’ rule and conditional probability
•     Total probability
•     Bayes’ rule application

Week 2 - Maths & Statistics Primer

•     Probability distribution
•     Binomial distribution
•     Central limit theorem
•     Manipulating normal variables

Week 3 - Python Primer

•     Operating systems overview
•     Variables in python

Week 4 - Python Primer

•     Creating and managing lists
•     Numerical lists
•     Tuples
•     Dictionaries in python

Week 5 - Python Primer

•     Boolean variables
•     Conditional variables
•     About functions
•     Python demonstration and code manipulation

Week 6 - Descriptive Analytics 

•     What is data?
•     Data and decision making

Week 7 - Descriptive Analytics

•     Estimate statistics of a data set
•     Maximum likelihood estimation
•     Detection and quantification of correlation

Week 8 - Descriptive Analytics

•     Outliers
•     Linear regression
•     Real-life applications

Week 9 - Predictive Analytics (4 weeks)

•     Introduction to machine learning
• Machine learning process
• Supervised learning

Week 10 - Predictive Analytics

• Forecasting vs inference
• Using nearest neighbours for classification problems
• Predict outcomes in a business context using regression trees
• Classify data using support vector machines

Week 11 - Predictive Analytics

• Measure similarity of data clusters
• Predict outcomes for different clusters
• Machine learning in the real world

Week 12 - Prescriptive Analytics

•     Foundations of linear programming
•     Optimisation problems
•     Production planning problem
•     Capital budgeting problem

Week 13 - Prescriptive Analytics

•     Identifying the constraints
•     The optimal solution
•     Solving the problem in Excel
•     Model business problems as linear programmes

Week 14 - Prescriptive Analytics

•     Integer programming
•     Optimisation models
•     Tricks-of-the-trade for business decisions
•     Real-life applications

  Text books

• Liba. (2020). Guide to Business Data Analytics. International Institute of Business Analysis
• ●  Turban, Efraim., Delen, Dursun., & Sharda, Ramesh. (2021).Business Intelligence, Analytics, and Data Science: A Managerial Perspective. Kindle Edition. Pearson

Course Description This subject goes beyond high-level foundational theory and the hypothetical to provide a fully immersive deep-dive into the skills, methods and tools employed by service designers everyday, whilst adding in some exclusive methods, teachings, content, field trips and surprises along the way.   Course Objectives

• Students can build differentiation, loyalty, and long-term business value by meeting their customers’ needs and exceeding their expectations
• Students will understand the interactions people have with your company and surface problem areas and opportunities through a customer journey map.
• Students will focus their efforts by choosing the most impactful moments to design.
• Students can enable others to understand and execute their vision with a service blueprint.

  Course Outline Week 1 - Module 1 Course Orientation, Introduction to Service Design Week 2 : Module 2 Becoming Human-Centred, Empathy Experiments, Building EQ, Empathy Mapping, Behavioural Science Week 3 : Module 4 Developing a Creative Mindset, Lateral Thinking, Workshop Facilitation, Co-Design & Collaboration, Ideation & Brainstorming Week 4 : Module 5, Project Planning & Risk, Agile, Feature Prioritisation, Minimum Viable Services, Roadmaps & Kanban Week 5 : Module 7 Analysing a Brief, Exploration Areas, Scope and Remit, Individual Project Briefing Week 6 : Module 8, Research Design, Sampling, Qualitative Methods, Quantitative Methods Week 7 : Module 11 Journey / Experience Mapping, Pain Intensity Measurement, User Solutions, Impact Assessment, Opportunity Prioritisation, Service Vision Statement Week 8 : Module 12 Brand, Equity & Value, Key Attributes, Experience Principles Week 9 : Module 15 Physical Prototyping, Role Play & Bodystorming, Scripting & Staging, Desktop Walkthroughs, Digital Prototyping, Usability Testing Week 10 : Module 17 Touchpoint Development, Signposting, Set Design & Flow, Evidencing, Communications Design, Staff Onboarding, Training & Tools Week 11 : Module 18 Service Blueprints, Service Specifications, Presenting & Storytelling Dress Rehearsals   Text books Stickdorn, Marc.,Schneider, Jakob. (2012) . This is Service Design Thinking: Basics, Tools, Cases. 1^st Edition. Wiley

Course Description Describes the relationship that needs to be established between innovation, business strategy, and project management to turn a creative idea into a reality.  We will explore the importance of identifying the components of an innovative culture, existing differences, challenges, and the new set of skills needed in innovation project management Course Objectives

•     Students can explain the links needed to bridge innovation, project management, and business strategy
• Students can describe the different types of innovation and the form of project management each require
• Students can identify the differences between traditional and innovation project management, especially regarding governance, human resources management challenges, components of an innovative culture and competencies needed by innovation project managers
• Students can establish business value and the importance of new metrics for measuring and reporting business value
• Students can relate innovation to business models and the skills needed to contribute in the business model development
• Students can recognize the roadblocks affecting innovation project management and their cause to determine what actions can be taken
• Students can determine the success and failure criteria of an innovation project

Course Outline

• Big Ambitious Ideas
• Customer Validation
• Value Proposition
• Prototyping
• Branding & Marketing
• Mentor Idea Review
• Legal & IP
• Go to Market
• Product Development
• Selling and Revenue
• Fundraising Capital
• Hiring & Onboarding
• Growth & Scaling

Text books

•   Ries, Eric (2011). The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Currency