The Diploma in Data Science with a focus on Data Science Foundations aims to equip learners with fundamental knowledge, skills, and understanding of data science principles and techniques. The course delves into various aspects of data science, including data analysis, machine learning, statistical modeling, data visualization, and emerging trends in the field.
COURSE OUTLINE
- Introduction to Data Science
- Foundational Concepts in Data Analysis
- Statistical Methods for Data Science
- Machine Learning Fundamentals
- Data Visualization Techniques
- Emerging Trends in Data Science
STUDENT ACQUISITIONS
Upon completing the course, students will:
- Understand the role of data science in modern society and its significance across various industries.
- Develop foundational knowledge in data analysis, statistical methods, and machine learning techniques.
- Evaluate data science approaches from technical, ethical, and practical perspectives.
- Apply data visualization techniques to communicate insights effectively.
- Stay updated on emerging trends and advancements in the field of data science.
LEARNING METHODOLOGIES
The course employs a range of effective learning methodologies, including:
- Engaging with theoretical concepts to build foundational knowledge of data science principles.
- Encouraging independent exploration and analysis of data science techniques and their applications.
- Facilitating hands-on experience through practical exercises and data analysis projects.
- Promoting critical evaluation of research papers, case studies, and industry reports related to data science.
- Fostering logical thinking and problem-solving skills through simulation exercises and real-world data scenarios.
- Enhancing communication abilities for clear and effective presentation of technical concepts and data analysis outcomes.
