Programme Partner
Overview
Why Enrol in Data Science & Analytics for Strategic Decisions?
Enterprises across the globe are shifting their focus to data-driven goals and decision-making. In fact, the International Data Corporation reports that worldwide data will grow 61% to 175 zettabytes by 2025*. So, why is data science so important? Because it enables organisations to efficiently process and interpret data that can be used to make informed business decisions & drive growth, optimisation and performance.
In the online Data Science & Analytics for Strategic Decisions programme—offered by Singapore Management University—you can learn how to process and understand data that can be used to drive better, smarter decisions within your organisation.
- Next Course Starts On 26 September 2024 (Thu)
- Duration14 Weeks, Online 4-6 hours per week
- LevelAdvanced
- VenueOnline
Learning Objectives
Create and implement business strategies leveraging data science.
Make data-driven decisions to solve business problems using data insights.
Demonstrate how analytics can be combined with experiments to make data-informed recommendations for business growth.
Explain the key challenges and risks in data science projects.
Evaluate an organisation’s data strategy and recommend ways to achieve a sustainable competitive advantage.
Analyse organisational needs and drive business improvement through data science future trends.
PROGRAMME HIGHLIGHTS
90+ Video Lectures
30 Assignments
10+ Industry Examples
6 Discussion Boards
6 Case Studies
3 Live Sessions with Faculty
Topics/Structure
- Key terminologies of data science
- Different levels of data analytics and their significance to decision-making
- Data features and insights to attain sustainable competitive advantage
- Applications of data analytics and its role in creating new business opportunities
- Analytical approach to resolve a business problem
- Is your organisation is data-driven
- Trends in data and obtaining related insights to enhance business performance
- Impact an organisation’s omnichannel strategies have on sales
- How to identify appropriate data/insights
- Comparison of independent data sets to obtain insights
- How to apply strategic decision-making using said techniques
- Regression to analyse the strength/impact of variables
- Predict variable impact using optimal model fit and regression effects
- Logistic regression model to test and predict expected outcomes
- Apply predictive analytics to organisational events to advance strengths and counter threats
- Correlation and causality and their significance to enhancing business performance
- Experimentation for business problems to make effective inferences
- Multivariate, A/B and Multi-Armed Bandit testing
- Effectiveness of using experimental design to make data-informed recommendations for business growth
- Recommendation Systems
- Recommendations and Ranking
- Collaborative Filtering
- Personalized Recommendations
- ML and its role in driving organisational productivity
- Apply ML algorithms to achieve optimal analytical accuracy
- Programme-building facets of neural networks and deep learning
- Combine analytics with experiments to produce effective business strategies
- Decision Making Under Uncertainty
- Bayesian Decision Making
- Simulations to make decisions under uncertainty
- Optimal Decision Making
- Linear Optimisation
- Sensitivity Analysis and Shadow Price
- Driving digital transformation within the organisation
- Change management: The role of data analytics, machine learning and its applications
- Aligning organisations and teams for data-driven approaches
- Making the business case for Data Science
- Data Storytelling with Visualisation using Tableau
- Disruptive innovation
- Distilling value from analytics
- Developing a strategy roadmap, privacy implications, traps and myths
- Customer-centric analytics in retail and media
- Business process analytics
- Domain exposure
- Key challenges to data science projects and their solutions
- Delta Framework and Delta Plus Model
- Project-level risks and examples of failed data science projects
- Predict the success of big data project using DATA technique
- Drivers, expected outcomes, and technology enablers for Industry 4.0
- Components for AI success
- Challenges in the implementation of AI in systems
- Evaluate an organisation’s digital transformation journey and sustain a competitive advantage
- Overview of ChatGPT and OpenAI
- Timeline of NLP and Generative AI
- Frameworks for understanding ChatGPT and Generative AI
- Implications for work, business, and education
- Business roles to leverage ChatGPT
- Futureproofing organisations to incorporate Generative AI into workflow
- Prompt engineering for fine-tuning outputs
- Safeguards and risk mitigation measures
Assessment
Schedule
Start Date(s) : Thu, 09/26/2024 - 12:00
Intake Information :
Refer to Online Singapore Management University Courses - Emeritus - Online Certificate Courses | Diploma Programs for the latest updates on application dates and discounts.
For more enquiries, please email to monica.taneja@emeritus.org or ruswelt.pereira@emeritus.org.
Alternatively, you may also write to us at exd@smu.edu.sg for any urgent matters related to the programme.