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Updated in [May 25th, 2023]

This course, Coding Interview Preparation, is the final course in the professional certificate program. It will help students prepare for the unique aspects of a coding job interview, with approaches to problem-solving and computer science foundations needed to land the job. Students will gain strategic insights and tips for successful interviewing.

By the end of this course, students will have knowledge of appropriate communication during a coding interview, successful interviewing strategies, using pseudocode, the fundamentals of computer science, the capabilities of data structures and how to implement them, how to review data structures in the context of coding interviews, the concept of algorithms and common approaches to working with them, how to visualize an algorithm, and combining new and previously learned coding patterns to solve problems.

Ideally, students should have completed all the courses in this professional certificate before taking this course.

[Applications]
Upon completion of this course, learners should be able to apply the knowledge and skills gained to prepare for coding interviews. They should be able to use pseudocode to explain their solutions, understand the fundamentals of computer science, and review data structures in the context of coding interviews. Learners should also be able to visualize algorithms, combine new and previously learned coding patterns to solve problems, and use appropriate communication during a coding interview.

[Career Paths]
1. Software Engineer: Software engineers are responsible for designing, developing, and testing software applications. They must have a strong understanding of computer science fundamentals, such as data structures, algorithms, and software design. As technology advances, software engineers must stay up-to-date on the latest trends and tools to ensure their applications are secure and efficient.

2. Data Scientist: Data scientists are responsible for analyzing large datasets to uncover patterns and insights. They must have a strong understanding of mathematics, statistics, and computer science fundamentals. As data science becomes more prevalent, data scientists must stay up-to-date on the latest trends and tools to ensure their analysis is accurate and efficient.

3. Machine Learning Engineer: Machine learning engineers are responsible for developing and deploying machine learning models. They must have a strong understanding of mathematics, statistics, and computer science fundamentals. As machine learning becomes more prevalent, machine learning engineers must stay up-to-date on the latest trends and tools to ensure their models are accurate and efficient.

4. DevOps Engineer: DevOps engineers are responsible for automating the deployment and management of software applications. They must have a strong understanding of computer science fundamentals, such as data structures, algorithms, and software design. As technology advances, DevOps engineers must stay up-to-date on the latest trends and tools to ensure their applications are secure and efficient.

[Education Paths]
1. Bachelor of Science in Computer Science: A Bachelor of Science in Computer Science is a four-year degree program that provides students with a comprehensive understanding of computer science fundamentals, such as programming, software engineering, and computer architecture. This degree is ideal for those looking to pursue a career in software development, computer engineering, or data science. Developing trends in this field include artificial intelligence, machine learning, and cloud computing.

2. Master of Science in Computer Science: A Master of Science in Computer Science is a two-year degree program that provides students with an advanced understanding of computer science topics, such as algorithms, data structures, and computer networks. This degree is ideal for those looking to pursue a career in research, software engineering, or data science. Developing trends in this field include natural language processing, robotics, and blockchain technology.

3. Doctor of Philosophy in Computer Science: A Doctor of Philosophy in Computer Science is a four-year degree program that provides students with an in-depth understanding of computer science topics, such as artificial intelligence, machine learning, and computer networks. This degree is ideal for those looking to pursue a career in research, software engineering, or data science. Developing trends in this field include quantum computing, augmented reality, and cybersecurity.

4. Master of Business Administration in Information Technology: A Master of Business Administration in Information Technology is a two-year degree program that provides students with a comprehensive understanding of business and technology topics, such as project management, information systems, and data analytics. This degree is ideal for those looking to pursue a career in business management, IT consulting, or data science. Developing trends in this field include cloud computing, big data, and digital transformation.