• Providing a strong foundation in data science: The programme aims to provide participants with a solid understanding of the fundamental concepts, theories, and principles of data science.
• Developing technical skills: The programme focuses on developing participants' technical skills in data analysis, machine learning, data visualization, and big data technologies.
• Developing practical experience: Participants will work on industry-relevant projects and case studies to gain practical experience in data science.
• Preparing for real-world applications: The programme prepares participants for real-world applications of data science in different industries such as healthcare, finance, and marketing.
• Encouraging collaboration and teamwork: Participants will have the opportunity to work in teams on group projects, developing their collaboration and teamwork skills.
• Emphasizing ethical considerations: The programme emphasizes ethical considerations in data science, including data privacy, security, and bias.
• Enhancing career opportunities: Upon completion of the programme, participants will have enhanced career opportunities in data science or related fields.

PROGRAMME OUTCOMES

• Understanding of data science concepts: Participants will have a solid understanding of the fundamental concepts, theories, and principles of data science, including statistical analysis, machine learning algorithms, data visualization, and big data technologies.
• Proficiency in data analysis: Participants will learn how to collect, clean, and analyze large datasets using popular programming languages such as Python and R. They will also learn how to use tools such as SQL and Hadoop to manage and process big data.
• Application of data science in real-world scenarios: The programme emphasizes the application of data science in different industries such as healthcare, finance, and marketing. Participants will work on industry-relevant projects and case studies to gain practical experience in data science.
• Ability to communicate data insights: Participants will learn how to communicate complex data insights to stakeholders using data visualization techniques, dashboards, and reports.
• Collaboration and teamwork: Participants will have the opportunity to work in teams on group projects, developing their collaboration and teamwork skills.
• Ethical considerations: Participants will learn about ethical considerations in data science, including data privacy, security, and bias.
• Career advancement: Upon completion of the programme, participants will be equipped with the skills and knowledge needed to tackle complex data related challenges in their organizations. They will have enhanced career opportunities in data science or related fields.

What you’ll learn

• Python & Python Libraries (NumPy, Pandas, Scikit-learn, and TensorFlow)
• R & R Libraries (dplyr, ggplot2, caret, and tidyr)
• SQL
• Hadoop & Hadoop Components (HDFS, MapReduce, and Hive)
• Tableau
• Excel
• SAS
• Apache Spark