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دوراتنا
Python Programming Fundamentals
This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
An Introduction to Logic for Computer Science
Logic plays a fundamental role in computer science. This course is designed to equip you with a solid understanding of the fundamental principles of logic and their relevance in the field of computer science. In this course, you'll explore proposition logic and discover its practical applications in problem-solving, algorithm design, and the development of intelligent systems. By engaging in hands-on exercises, exploring real-world examples, and participating in discussions, you'll develop strong logical reasoning and critical thinking skills.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Dynamic Programming, Greedy Algorithms
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform.
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Course by
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Self Paced
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38 ساعات
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الإنجليزية
Basic Robotic Behaviors and Odometry
"Basic Robotic Behaviors and Odometry" provides you with an introduction to autonomous mobile robots, including forward kinematics (“odometry”), basic sensors and actuators, and simple reactive behavior. This course is centered around exercises in the realistic, physics-based simulator, “Webots”, where you will experiment in a hands-on manner with simple reactive behaviors for collision avoidance and line following, state machines, and basic forward kinematics of non-holonomic systems.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Algorithms for Searching, Sorting, and Indexing
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others.
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Course by
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Self Paced
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35 ساعات
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الإنجليزية