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David Joyner

“Introduction to Computing in Python” is a series of courses built from Georgia Tech’s online for-credit version of CS1301: Introduction to Computing. The series is designed to take you from no computer science background whatsoever to proficiency in the basics of computing and programming, specifically in the popular programming language Python. Rated as one of the most in-demand and beginner-friendly programming languages, Python training will give you a solid foundation not only for Python code but for further studies in computer science.

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“Introduction to Computing in Python” is a series of courses built from Georgia Tech’s online for-credit version of CS1301: Introduction to Computing. The series is designed to take you from no computer science background whatsoever to proficiency in the basics of computing and programming, specifically in the popular programming language Python. Rated as one of the most in-demand and beginner-friendly programming languages, Python training will give you a solid foundation not only for Python code but for further studies in computer science.

The syllabus and course material has been used at Georgia Tech for its for-credit CS1301 class for over a year. Over 400 students on campus have completed this version of the course, and our analysis shows that they exit the course with the same learning outcomes as students taking the traditional on-campus version. This Professional Certificate uses the same instructional material and assessments as learning Python on campus, giving you a Georgia Tech-caliber introduction into the field of computing at your own pace.

This Professional Certification course follows a unique design. Students will cover the general, fundamental principles of computer science—which are applicable to any programming language like javascript or R — and then rapidly transition to those same programming concepts in Python. Short videos (2-3 minutes each) are rapidly interleaved with live programming problems, real-world examples, and multiple-choice questions to give you constant feedback on your progress and understanding.

What you'll learn

  • The fundamental design cycle of computer science and computer programming: writing code, executing it, interpreting the results, and revising the code syntax based on the outcomes.
  • Usage of the fundamental atoms of programming: variables, mathematical operators, logical operators, and boolean arithmetic.
  • Control structures for developing dynamic programs, including Python libraries: conditionals, loops, functions, and error handling.
  • The core data structures for creating useful programs: strings, lists, dictionaries, and file manipulation.
  • Previews of the next big topics in computer science: object-oriented programming skills, and computer algorithms.

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What's inside

Four courses

Computing in Python I: Fundamentals and Procedural Programming

(47 hours)
This course starts from the basics of how a computer interprets lines of code and how to write programs. By the end of this course, you'll be able to write small programs in Python that use variables, mathematical operators, and logical operators.

Computing in Python II: Control Structures

(47 hours)
Building on your prior knowledge, this course gets into the meat of programming. It starts by covering the fundamentals of control structures, then moves on to four common control structures in Python: conditionals, loops, functions, and error handling. By the end of this course, you'll be able to write complex programs in Python that perform useful reasoning.

Computing in Python IV: Objects & Algorithms

(47 hours)
Complete your introductory computer science knowledge with this final course on objects and algorithms. Learn object-oriented programming to develop programs that leverage your natural understanding of problems. Analyze program complexity and efficiency through algorithms. Certify your broader Introduction to Computing knowledge with a comprehensive exam.

Computing in Python III: Data Structures

(47 hours)
Build on your Python knowledge by studying complex data structures, including strings, lists, dictionaries, and file input and output. This course covers:

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