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Updated in [June 30th, 2023]

This course provides an overview of Data Science and its components. It will discuss how Data Science should be defined and what components make up Data Science. It is important to note that this course does not provide coding lessons, and is more focused on the big picture and business aspects of Data Science projects. Participants will gain an understanding of the fundamentals of Data Science and its components.

[Applications]
The application of this course is to provide a basic understanding of the components of Data Science. It is recommended that those who have completed this course should further their knowledge by exploring the various aspects of Data Science, such as coding, data analysis, and machine learning. Additionally, it is suggested that those who have completed this course should look into the business aspects of Data Science, such as project management, data visualization, and data storytelling.

[Career Paths]
Data Science is a field of study that combines mathematics, statistics, computer science, and domain knowledge to extract insights from data. It is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science is used to analyze data from various sources, such as databases, web applications, and social media, to gain insights and make predictions.

A Data Scientist is a professional who uses data to solve problems and make decisions. They use a variety of tools and techniques to analyze data and develop models to make predictions. Data Scientists are responsible for collecting, cleaning, and analyzing data, as well as developing and testing models. They also need to be able to communicate their findings to stakeholders and make recommendations based on their analysis.

The development trend of Data Science is rapidly growing. Companies are increasingly relying on data to make decisions and are investing heavily in Data Science teams. Data Scientists are in high demand and the job market is expected to continue to grow. Companies are looking for Data Scientists with a wide range of skills, including programming, machine learning, statistics, and domain knowledge. As the demand for Data Scientists continues to grow, the job market is expected to become more competitive.

[Education Paths]
Data Science is an interdisciplinary field that combines mathematics, statistics, computer science, and domain knowledge to extract insights from data. It is a rapidly growing field that is used to analyze large datasets to uncover patterns, trends, and correlations. Data Science is used to make predictions, build models, and develop algorithms that can be used to solve complex problems.

Data Science is a combination of several disciplines, including mathematics, statistics, computer science, and domain knowledge. It involves the use of data-driven techniques to uncover patterns, trends, and correlations in large datasets. Data Science also involves the use of machine learning algorithms to make predictions and build models.

The educational path for learners interested in Data Science is to first obtain a Bachelor's degree in a related field such as mathematics, statistics, computer science, or engineering. After completing a Bachelor's degree, learners can pursue a Master's degree in Data Science or a related field. This will provide learners with the necessary skills and knowledge to work in the field of Data Science.

The development trend for Data Science is to focus on the use of artificial intelligence (AI) and machine learning (ML) to analyze large datasets. AI and ML are used to uncover patterns, trends, and correlations in data. AI and ML are also used to make predictions and build models. As the field of Data Science continues to evolve, learners should stay up to date with the latest technologies and trends in the field.

Course Syllabus

Actionable Insight

Data - Basic Concepts

CRISP-DM : A Process Framework based on Scientific Method

Multidisciplinary Knowledge and Computing Technologies