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Updated in [May 25th, 2023]

This online course, Creating a Systematic Literature Review, provides an overview of the process of conducting a systematic literature review. Participants will learn how to identify relevant literature, develop a search strategy, and evaluate the quality of the literature. The course will also cover the use of software tools to manage the literature review process. Upon completion of the course, participants will have the skills and knowledge to conduct a systematic literature review.

[Applications]
This online course provides an introduction to the systematic literature review process. It covers topics such as how to develop a research question, how to search for relevant literature, and how to evaluate and synthesize the literature. After completing this course, participants should be able to apply the systematic literature review process to their own research projects. Suggestions for application include developing a research question, conducting a comprehensive literature search, critically evaluating the literature, and synthesizing the literature to draw meaningful conclusions. Additionally, participants should be able to apply the systematic literature review process to other research projects, such as developing a research proposal or conducting a meta-analysis.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large amounts of data and using it to develop insights and solutions. They use a variety of tools and techniques to uncover patterns and trends in data, and then use this information to create predictive models and algorithms. Data Scientists are in high demand due to the increasing amount of data being generated and the need for organizations to make sense of it. The development of new technologies such as artificial intelligence and machine learning are also driving the demand for Data Scientists.

2. Business Analyst: Business Analysts are responsible for analyzing business processes and developing solutions to improve efficiency and effectiveness. They use a variety of tools and techniques to identify areas of improvement, and then develop strategies to address them. Business Analysts are in high demand due to the need for organizations to become more efficient and effective. The development of new technologies such as artificial intelligence and machine learning are also driving the demand for Business Analysts.

3. Research Analyst: Research Analysts are responsible for conducting research and providing insights into a variety of topics. They use a variety of tools and techniques to uncover patterns and trends in data, and then use this information to develop reports and recommendations. Research Analysts are in high demand due to the need for organizations to make sense of large amounts of data. The development of new technologies such as artificial intelligence and machine learning are also driving the demand for Research Analysts.

4. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data systems. They use a variety of tools and techniques to create data pipelines, databases, and other data systems. Data Engineers are in high demand due to the need for organizations to store and process large amounts of data. The development of new technologies such as artificial intelligence and machine learning are also driving the demand for Data Engineers.

[Education Paths]
1. Bachelor of Science in Computer Science: This degree path provides students with a comprehensive understanding of computer science, including programming, software engineering, and computer systems. It also covers topics such as artificial intelligence, machine learning, and data science. As technology continues to evolve, this degree path is becoming increasingly popular and in demand.

2. Bachelor of Science in Information Technology: This degree path focuses on the application of technology to solve problems and create solutions. It covers topics such as software development, database management, and network security. With the rise of digital transformation, this degree path is becoming increasingly important for businesses and organizations.

3. Master of Science in Data Science: This degree path focuses on the analysis and interpretation of large datasets. It covers topics such as machine learning, data mining, and predictive analytics. As data becomes increasingly important for businesses and organizations, this degree path is becoming increasingly popular and in demand.

4. Master of Science in Artificial Intelligence: This degree path focuses on the development of intelligent systems and algorithms. It covers topics such as natural language processing, computer vision, and robotics. As artificial intelligence continues to evolve, this degree path is becoming increasingly important for businesses and organizations.