Essential Python & Data Structures
Master Python programming and data structures in this advanced 5-week course from Columbia University. Perfect for building AI programming foundations.
Master Python programming and data structures in this advanced 5-week course from Columbia University. Perfect for building AI programming foundations.
This comprehensive course offers a deep dive into Python programming and data structures, designed as essential preparation for advanced AI and computer science coursework. Students will explore fundamental Python concepts including control structures, variables, data types, and object-oriented programming. The course serves as a crucial foundation for those seeking to establish strong programming skills, particularly in preparation for AI-related studies. Through self-paced learning and practical assessments, students gain hands-on experience with Python while developing a solid understanding of essential data structures. The course combines theoretical knowledge with practical application, ensuring learners develop the technical proficiency needed for advanced computational work.
Instructors:
English
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What you'll learn
Understand key components of Python programming including control structures and data types
Master object-oriented programming concepts and implementation
Develop proficiency in working with various data structures
Gain practical experience through hands-on programming exercises
Build a strong foundation for advanced AI programming courses
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
FullTime access
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Module Description
This course provides a comprehensive introduction to Python programming and data structures, serving as essential preparation for advanced AI and computer science studies. The curriculum covers fundamental Python concepts including variables, data types, control structures, and object-oriented programming principles. Students will learn how to design and implement efficient data structures while developing strong programming fundamentals. The course emphasizes practical application through hands-on coding exercises and self-assessment opportunities, ensuring students build both theoretical understanding and practical programming skills.
Fee Structure
Instructor
4 Courses
Expert in Natural Language Processing at Columbia University
Dr. Daniel Bauer is a Senior Lecturer in the discipline of natural language processing in the Department of Computer Science at Columbia University. His research focuses on developing systems that can accurately interpret natural language in multimodal environments and linguistic discourse, with a particular emphasis on the semantics of natural language and efficient translation between surface text, syntax, and semantics. Bauer's work utilizes deep, formal representations of language meaning, applicable to areas like machine translation and natural language user interfaces. With degrees in cognitive science from the University of Osnabrück, language science and technology from Saarland University, and a PhD in computer science from Columbia University, Bauer brings a multidisciplinary approach to his research. His expertise lies in syntactic and semantic parsing, combining machine learning techniques with linguistically inspired formal models. Bauer's innovative work includes using hyperedge replacement graph grammars to construct meaning representations and exploring language grounded in other modalities like formal knowledge bases, 3-D scenes, vision, and robotics. Through his research and teaching, Bauer contributes significantly to advancing natural language processing systems and their applications in various fields
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