Certificate of Advanced Studies in Data science leadership , 10 ECTS
Join our CAS programme in Data Science Leadership. This course is designed for professionals who want to master data science leadership. Study real-world use cases and understand the challenges faced by data-driven organisations. Learn how to optimise team structures, prioritise projects, and allocate resources effectively. Gain insights into managing data initiatives.
Data is a key asset in today’s business world. It drives innovation and informs strategic decisions. A strong data strategy is critical for marketing, customer management, and product quality. There is a high demand for leaders who can bridge the gap between business and technology teams.
More informationBy completing this programme, you will gain:
- Efficient co-creation: Enhance mutual understanding between business and technology leaders, fostering better communication and collaboration. Improve the ability of technology and business teams to work together efficiently on technology transformation projects.
- Real-world application: Focus on real-world problems and use cases, ensuring the immediate application of learning for practical and impactful results.
- Flexible learning environment: The fully online format allows participants to learn at their own pace, balancing education with work commitments.
- Personalised support and networking: Benefit from personalised support from lecturers and opportunities to network with peers and experts, enhancing your learning and professional connections.
Our programme equips leaders with the skills to lead data science projects. It fosters understanding, sets clear goals, and improves communication between business and technology teams. Enrol in the CAS in Data Science Leadership to advance your career as a data-driven leader.
Leverage data assets
Enhance product quality, improve customer experience and increase profitability.
Lead with confidence
Develop leadership skills to guide and inspire your data science team towards achieving organisational goals.
Optimise team performance
Foster a collaborative environment that maximises the productivity and effectiveness of your multidisciplinary teams.
Objectives
Participants will strengthen their ability to identify and develop data science talents, establish a robust data infrastructure, monetise data assets, prioritise, and manage data projects, and address legal and ethical data concerns – essential elements for both personal career advancement and organisational growth.
By attending, you will learn how to:
- Confidently lead and optimise the performance of data science teams.
- Utilise data-driven insights for impactful and strategic decision-making.
- Drive business growth through effective data-driven leadership strategies.
- Leverage data assets to enhance product quality, improve customer experience, and increase profitability.
- Gain a comprehensive understanding of data infrastructure, ethical considerations, and legal compliance in data use.
- Prioritise and manage data projects efficiently, aligning them with organisational goals.
- Foster effective communication and collaboration between business and tech teams.
Your learning journey
select and combine
M01 Creating value with data science
Explore strategies for monetising data within organisations. Learn how leveraging data can impact marketing strategies, reduce
production costs, and enhance customer experience. By the end of the module, you will be equipped to unlock the potential of data to drive revenue and profit.
2 ECTS
M02 Data infrastructure Fundamentals
Understand the essential elements of a solid data infrastructure. Explore options for storing data in a structured, accessible, and manageable way. Gain a foundational understanding of database systems, cloud computing, and data warehousing concepts.
2 ECTS
M03 Developing Data Science Talent
Develop effective data science teams and foster collaboration among business, science, and engineering teams. Learn strategies to drive innovation and improve team performance. Recruit, train and manage data science teams.
2 ECTS
M04 Data science project management
Learn the fundamental elements of data science project management and prioritisation. Analyse methods for aligning projects with organisational goals, optimising resource allocation, and proactively identifying project risks.
2 ECTS
M05 Data ethics and compliance
Examine ethical considerations and regulatory compliance in data use and decision-making. Gain the skills to navigate ethical aspects and master legal compliance in data management.
2 ECTS
Meet your programme director
Prof. Dr. Anthony Strittmatter
Programme Director and Professor in Economics
Anthony Strittmatter is a Full Professor of Applied Econometrics at UniDistance Suisse and has more than thirteen years of experience in causal inference, machine learning and quantitative analysis.
He worked as a Senior Economist in Amazon's EU Economic Decision Science team in London, where he applied data science techniques to improve business recommendations, which now helps him provide you with practical insights into data-driven strategies.
Prof. Dr. Strittmatter has taught at École Polytechnique in Paris and HSG St. Gallen, and is affiliated with the University of Johannesburg and CESifo in Munich. His research has been supported by the Swiss National Science Foundation and the French Research Council and has been published in prestigious journals and presented at international conferences.
Your flexible online learning experience
The programme is delivered through a comprehensive e-learning platform, providing access to all necessary learning materials, including scientific documents, supplementary literature, tasks, assignments, exercises and videos.
E-Learning-platform
The platform provides all necessary learning materials, discussion forums, and support tools. You can access resources anytime.
Collaborative group work
You engage in group work during online meetings to solve practical problems, enhancing teamwork and peer learning.
Interactive virtual classes
Modules include virtual classes for discussions, case studies, and practical examples to deepen understanding and apply theoretical knowledge to real-world scenarios.
Peer-to-peer learning and feedback
You will share projects and receive feedback from peers and lecturers, enhancing learning through a collaborative feedback loop.
Personalised learning experience
Courses are tailored to your needs, with lecturers adapting content based on feedback and developing personalised use cases.
Continuous support and mentorship
Lecturers provide ongoing support through discussion forums and live sessions, with personalised mentorship offering tailored guidance.
Benefits for your firm
Enrolling employees in the CAS in Data Science Leadership programme offers key benefits for your firm:
- Innovation and Efficiency: Identify new business opportunities, streamline operations, and reduce costs through better data analysis.
- Enhanced Customer Insights: Understand customer behaviour and preferences, leading to more personalised marketing strategies and improved customer satisfaction.
- Talent Development: Invest in employee growth, enhancing job satisfaction and retention, and attracting top talent.
- Risk Management: Use predictive analytics to foresee and mitigate potential risks effectively.
- Strategic Alignment: Ensure data initiatives align with your company’s goals for more informed and effective planning.
- Improved Project Outcomes: Enhance project management with better data tracking and reporting and integrate new technologies to keep the organisation agile and competitive.
About UniDistance Suisse
UniDistance Suisse is Switzerland's leading institution for distance university studies, accredited in accordance with the Swiss Higher Education Act (HEdA). Established in 1992, we offer Bachelor's, Master's and continuing education programmes in French, German and English, which enable adult students to reconcile study, work and personal life thanks to flexible, innovative teaching based the the latest technology. Recognised by the Swiss Confederation in 2004, we guarantee academic excellence and degrees equivalent to any other Swiss university.
30+
Years of experience in online learning
23'467
Alumni across the world
160%
Students increase since 2002
38
Student average age
More details about this Certificate of Advanced Studies in Data Science Leadership
Teaching team
The target audience for a continuing education program in Data Science Leadership typically includes:
- Mid to Senior-Level Data Professionals: Data scientists, data analysts, data engineers, and data architects looking to advance their careers into leadership roles. Professionals with significant experience in data roles who want to develop management and strategic skills.
- Managers and Leaders in Data-Driven Organizations: Current managers, team leaders, and directors in data science or analytics teams aiming to enhance their leadership skills. Professionals responsible for leading data teams or overseeing data-related projects and initiatives.
- Technical Professionals Transitioning to Leadership Roles: Software engineers, IT specialists, and other technical professionals seeking to move into data science leadership positions. Individuals with a technical background who want to develop strategic thinking and leadership capabilities.
- Business Leaders and Executives: Executives and senior managers who need to understand data science to make informed strategic decisions. Business leaders aiming to leverage data science for organisational growth and competitive advantage.
- Professionals from Related Fields: Individuals from related fields such as business intelligence, operations research, and statistics looking to pivot to data science leadership. Consultants and advisors specializing in data-driven decision-making and strategy.
- Aspiring Entrepreneurs and Innovators: Entrepreneurs and startup founders looking to harness data science for their business ventures. Innovators aiming to lead data-driven initiatives and drive technological advancements.
Enrolling in the CAS in Data Science Leadership programme offers several clear benefits:
- Practical Insights and Skills: Study real-world scenarios to understand opportunities and challenges in data-centric organizations.
- Effective Leadership and Project Management: Develop skills in project management and team leadership tailored to data-driven environments. Learn to optimize team structures, prioritize projects, and use resources efficiently.
- Data-Driven Decision Making: Use data to make decisions that drive business growth and improve performance.
- Career Advancement: Gain skills and knowledge that can significantly boost your career as a data science leader.
This programme gives you the skills and confidence to lead data science teams, drive strategic decisions, and help your organization succeed.
Each module is flexible and can be selected independently, allowing you to build a program that fits your interests. Learn from experts in both academia and the private sector, providing a complete view of data science leadership.
Pursuing continuing education in data science leadership can open up a range of advanced career opportunities, combining technical data science skills with strategic leadership capabilities. Here are some examples you can consider:
- Chief Data Officer (CDO): Responsible for overseeing the data management strategy, data governance, and utilization of data as an asset. Work closely with other C-suite executives to integrate data-driven decision-making into the organization’s overall strategy.
- Data Science Manager/Director: Leads a team of data scientists and analysts, managing projects, setting goals, and ensuring the quality and impact of data science initiatives. Bridges the gap between data science teams and other departments, facilitating collaboration and communication.
- Analytics Director/Head of Analytics: Oversees the analytics function within an organization, focusing on the strategic use of data analytics to drive business decisions. Taking responsibilities for aligning analytics efforts with business goals and demonstrating the value of analytics to stakeholders.
- AI/ML Operations Lead: Manages the deployment and operationalization of AI/ML models in production environments. Ensures the reliability, scalability, and performance of AI/ML solutions within the organization.
- Data Strategy Consultant: Works with organizations to develop and implement data strategies that support business objectives. Provides expertise in data governance, architecture, and analytics to help organizations maximize their data potential.
- Business Intelligence (BI) Director: Leads the BI team in developing and implementing business intelligence tools and solutions. Focuses on transforming data into actionable insights that support strategic decision-making.
- Innovation Lead in Data Science: Drives innovation in data science practices and technologies within an organization. Stays abreast of emerging trends and technologies, ensuring the organization remains competitive in the use of data science.
- Product Manager for Data Products: Manages the development and lifecycle of data-driven products and services. Collaborates with data scientists, engineers, and other stakeholders to deliver products that leverage data to solve customer problems.
- Data Governance Lead: Ensures that data policies, standards, and practices are in place and followed. Focuses on data quality, privacy, security, and compliance with relevant regulations.
- Head of Data Science Innovation Lab: Leads a dedicated team focused on exploring and prototyping new data science techniques and technologies. Encourages experimentation and rapid development of proof-of-concept models.
- Data-Driven Transformation Leader: Guides organizations through the process of becoming more data-centric. Works on change management, helping to build a data-driven culture and mindset across the organisation.
- Academic and Training Roles: Teach and mentor the next generation of data scientists and leaders. Develop curricula and lead training programs in data science and leadership.
Each of these roles requires a blend of technical data science skills, leadership abilities, strategic thinking, and the ability to communicate complex concepts to non-technical stakeholders. Continuing education in data science leadership equips you with the knowledge and skills to excel in these advanced roles, making you, a valuable asset in any organization looking to leverage data for strategic advantage.
- Unique Online Offering: UniDistance Suisse is the only university institute in Switzerland offering the CAS in Data Science Leadership entirely online, providing maximum flexibility and convenience.
- Flexible Learning: Study when and where you want. Twice a month, engage with fellow students and lecturers in virtual classrooms for discussions, teamwork, and interactive exercises based on real-life case studies.
- 24/7 Access to Resources: Access our e-learning platform anytime, with learning materials, academic resources, tasks, assignments, module videos, and quizzes available for independent study.
- Expert Lecturers: Learn from top professionals and experts in their fields, ensuring high-quality education.
- Accredited Institution: UniDistance Suisse is accredited under the Law on the Promotion and Coordination of Higher Education (LEHE). Our courses with ECTS credits are internationally recognized.
- Work-Life Balance: Our courses are designed to fit with your professional and family life, allowing you to balance your education with other commitments.
- This programme is given over five months. Each month focuses on a different theme.
- The virtual classes lasting an hour and a half are held on Wednesdays from 6.15 pm to 7.45pm.
- The course is offered once a year, in the spring semester.
- Each module is independent and can be follow individually. Each module is credited 2 ECTS
Every module lasts four weeks and is certified with 2 ECTS points (European Credit Transfer System), which corresponds to a study workload of approx. 50 to 60 hours per module.
One ECTS point corresponds to a study workload of 25 to 30 hours. You can find more information here.
Each module is evaluated separately. Moreover, participants will undertake an individual project based on a real problem faced by their organization. This project serves as a pivotal component of the learning journey through all the modules, allowing participants to apply all the concepts, methods, and approaches they have learned throughout the programme. The aim is to ensure that participants can immediately translate their new skills into practical and actionable solutions for their job roles.
The CAS Data science leadership is offered once a year in the spring semester. Virtual classes are planned on a fortnightly basis, on Wednesday evenings between 6.15 and 7.45 p.m.
Upon successful completion of all modules, UniDistance Suisse will award you the university continuing education certificate "Certificate of Advanced Studies (CAS) in Data science leadership".
You will receive 10 ECTS credits (European Credit Transfer System) for the entire CAS, which are awarded in accordance with Bologna guidelines and international standards.
If you decide to follow only one, or more modules, you will receive 2 ECTS for each completed module.
CHF 7800.- / CHF 1600.- per module.
10% off for UniDistance Suisse alumni
A minimum of 6 participants is required to start the programme.
The maximum number of students who can take part in the CAS « Data science leadership » is limited to 20.
The language of instruction and the literature used is English.