Master in Business Analytics & Data Science
1 Year
English
Swiss School of Research and Management
Code: MBADS
Programme Prelude:
The eMasters in Data Science and Business Analytics program offers a dynamic curriculum that empowers participants with a comprehensive understanding of data-driven decision-making. This online program is structured to provide flexibility, combining Core (C), Advanced Electives, and Domain Electives (E) modules.
Core Modules introduce fundamental concepts in data analysis and regression techniques, emphasizing practical application. Advanced Electives delve into machine learning, optimization, time series analysis, and causal inference, equipping students with advanced analytical tools.
Domain Electives allow students to specialize in areas like marketing analytics, financial analytics, social media analytics, supply chain analytics, and HR analytics, imparting industry-specific knowledge.
The program fosters hands-on experience, enhancing problem-solving skills and preparing students for real-world challenges. By the end, graduates possess a robust skill set that is highly relevant to the ever-evolving fields of data science and business analytics, making them sought-after professionals in the AI industry.
Teaching Philosophy:
Teaching Philosophy for the 1-Year Top-Up Program in Data Science and Business Analytics:
Our 1-Year Top-Up program in Data Science and Business Analytics builds on the foundation of knowledge and skills acquired in your previous education. The program is designed to offer a focused and intensive learning experience, tailored to the specific needs of professionals aiming to enhance their data analytics and business decision-making expertise.
- Advanced Specialization: We emphasize advanced specialization in core data science and business analytics subjects, enabling you to deepen your understanding of crucial concepts in the field.
- Real-World Application: Practical application of data analytics tools and techniques is at the heart of our teaching methodology. We guide you in translating theoretical knowledge into real-world problem-solving, ensuring you are well-prepared for challenges in the AI industry.
- Industry Integration: We foster strong connections with industry partners, providing you with opportunities for industry insights and hands-on experience. Guest lectures, case studies, and projects from leading professionals in the field are integrated into the program.
- Interactive Learning: Our online platform offers interactive learning, including live webinars, collaborative projects, and peer-to-peer interactions, creating a dynamic and engaging learning environment.
- Mentorship: You will have access to experienced mentors who provide guidance, support, and valuable insights as you navigate through complex data analytics challenges.
- Continuous Assessment: Regular assessments, quizzes, and projects will help you monitor your progress and provide timely feedback for improvement.
- Practical Projects: You will undertake practical data analytics projects, allowing you to apply your skills to real data sets and solve real-world problems.
- Career Development: The program places a strong emphasis on preparing you for career advancement, with career development services, networking opportunities, and industry connections.
Our teaching philosophy is centered on equipping you with the most up-to-date knowledge and practical skills required to excel in the field of data science and business analytics, ensuring you’re at the forefront of the AI industry.
Module Options:
Module 1: Advanced Data Analytics This module focuses on advanced data analytics techniques, including predictive modeling, advanced regression analysis, data mining, and advanced statistical analysis. Practical applications and case studies enhance your problem-solving skills.
Module 2: Big Data and Cloud Analytics In this module, you’ll delve into handling and analyzing large datasets using big data technologies and cloud computing. Topics include distributed computing, data storage, and processing frameworks, with hands-on experience in tools like Hadoop and Spark.
Module 3: Machine Learning and AI This module explores machine learning, neural networks, deep learning, and artificial intelligence. Gain practical experience in developing AI models for real-world applications and evaluating model performance.
Module 4: Business Intelligence and Data Visualization Emphasizing business intelligence tools and data visualization techniques, this module transforms data into actionable insights. Work with tools like Tableau, Power BI, and QlikView, and learn to create compelling visualizations and reports.
Module 5: Advanced Statistical Analysis Building on statistical knowledge, this module covers advanced statistical techniques and their applications in business decision-making. Topics include multivariate analysis, time series analysis, and advanced statistical tests.
These modules are designed to provide you with advanced and relevant skills in data science and business analytics, ensuring you’re well-prepared to excel in the AI industry without involving projects.
Opportunities:
These career opportunities reflect the diverse and highly sought-after skill set you’ll gain from the program, making you a valuable asset in various industries and positions where data-driven insights are essential.
- Data Scientist: Analyze complex data to extract valuable insights and make data-driven decisions.
- Machine Learning Engineer: Develop and implement machine learning algorithms for AI applications.
- Business Intelligence Analyst: Transform data into actionable insights to drive strategic decisions.
- Data Analyst: Focus on data preparation, analysis, and interpretation to support business improvement.
- AI Developer: Create AI applications, chatbots, and solutions across various industries.
- Big Data Engineer: Manage and analyze large datasets using big data technologies.
- Cloud Data Analyst: Leverage cloud computing and data analytics for scalable solutions.
- Data Consultant: Offer expertise in data analytics for data-driven decision-making.
- AI Researcher: Engage in cutting-edge AI research to advance the field.
- Business Analyst: Use data-driven insights to solve complex business challenges.
- Financial Analyst: Make informed investment and financial decisions with data analytics.
- Marketing Analyst: Optimize marketing campaigns and improve customer targeting.
- Healthcare Data Analyst: Enhance patient care and contribute to medical research through data analysis.
- Supply Chain Analyst: Optimize supply chain operations and logistics using analytics.
- Cybersecurity Analyst: Identify and mitigate cybersecurity threats through data analytics.