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Computational Thinking for Problem Solving
University of Pennsylvania via Coursera Help
- Pillars of Computational Thinking
- Computational thinking is an approach to solving problems using concepts and ideas from computer science, and expressing solutions to those problems so that they can be run on a computer. As computing becomes more and more prevalent in all aspects of modern society -- not just in software development and engineering, but in business, the humanities, and even everyday life -- understanding how to use computational thinking to solve real-world problems is a key skill in the 21st century. Computational thinking is built on four pillars: decomposition, pattern recognition, data representation and abstraction, and algorithms. This module introduces you to the four pillars of computational thinking and shows how they can be applied as part of the problem solving process.
- Expressing and Analyzing Algorithms
- When we use computational thinking to solve a problem, what we’re really doing is developing an algorithm: a step-by-step series of instructions. Whether it’s a small task like scheduling meetings, or a large task like mapping the planet, the ability to develop and describe algorithms is crucial to the problem-solving process based on computational thinking. This module will introduce you to some common algorithms, as well as some general approaches to developing algorithms yourself. These approaches will be useful when you're looking not just for any answer to a problem, but the best answer. After completing this module, you will be able to evaluate an algorithm and analyze how its performance is affected by the size of the input so that you can choose the best algorithm for the problem you’re trying to solve.
- Fundamental Operations of a Modern Computer
- Computational thinking is a problem-solving process in which the last step is expressing the solution so that it can be executed on a computer. However, before we are able to write a program to implement an algorithm, we must understand what the computer is capable of doing -- in particular, how it executes instructions and how it uses data. This module describes the inner workings of a modern computer and its fundamental operations. Then it introduces you to a way of expressing algorithms known as pseudocode, which will help you implement your solution using a programming language.
- Applied Computational Thinking Using Python
- Writing a program is the last step of the computational thinking process. It’s the act of expressing an algorithm using a syntax that the computer can understand. This module introduces you to the Python programming language and its core features. Even if you have never written a program before -- or never even considered it -- after completing this module, you will be able to write simple Python programs that allow you to express your algorithms to a computer as part of a problem-solving process based on computational thinking.
Susan Davidson and Chris Murphy
- united states
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Experiences in applied computational thinking, penn gse certificate, you are here, earn your certificate online: learn to incorporate coding, computational thinking, and basic programming in your pedagogy . .
The certificate program in Experiences in Applied Computational Thinking (EXACT) prepares K-12 educators to implement computational thinking in their teaching and learning spaces. Designed for beginners, this program helps teachers develop their own computational thinking and coding skills as well as those of their students. This certificate is a 30-week part-time program geared toward working professionals.
What Sets Us Apart
About the program.
The Experiences in Applied Computational Thinking (EXACT) program is an online certificate program that provides an introduction to computational thinking and coding for educators who have no prior experience with coding or computing in K-12 classrooms.
Cost $6660 ($3330 per semester)
Certificate/Licensure offered
- Penn GSE Certificate in Applied Computational Thinking
- Pennsylvania Act 48 credits
Professional development Equivalent of 12 Continuing Education credits
- Certificate
The Experiences in Applied Computational Thinking (EXACT) certificate program is designed by Penn GSE and Penn Engineering’s renowned GRASP Lab to provide educators with an understanding of computational thinking through experiential learning using current theory and practice in the field of computer science.
We welcome beginners to the program — beginners who would like to incorporate computational thinking in their pedagogy. Computational thinking can enhance students’ problem-solving skills, empowering them to become confident and successful problem solvers in an increasingly complex world. With this program, educators come to understand computational thinking, re-examine how computational thinking can fit into their current lessons, and become part of a community and professional learning network.
EXACT’s program of study develops teacher expertise in computational concepts (coding concepts such as loops, sequences, data), computational practices (problem solving practices that occur in coding such as debugging, reusing, remixing), and computational perspectives (understanding of themselves and their relation to a digital world around them). The program also introduces cutting-edge applications of computers in real-world contexts, such as natural language processing, computer vision, and robotics.
Specifically geared toward educators who have no prior experience with coding or computing in K-12 classrooms, the EXACT program will:
- Help you develop computational thinking skills and basic programming skills
- Serve as a starting point to advanced computer science education courses
- Encourage coding and computational thinking within the K-12 classroom environment.
Program of Study
The program modules follow the sequence below.
EDCE 588 and 589: Introduction to Computational Thinking
Participants begin the course by understanding the need for computational thinking in the 21st century classroom, and exploring ways in which it can be made explicit in their teaching spaces. Through an introductory coding platform, participants build introductory level computer science skills and explore the basics of coding languages. This develops the thinking skills and language around coding, such as variables, loops, and conditional statements.
EDCE 590 and 591: Introduction to Python and Machine Learning
In these modules, participants will be introduced to programming in Python, and will learn to program the Raspberry Pi. They will need to solve computational thinking problems using computer hardware, peripherals, and machine learning in a guided learning experience.
EDCE 592 and 593: Project-based Computational Thinking
Building on previous modules, participants use applications such as natural language processing or computer vision to solve a relevant problem. It culminates with an immersive project designed to apply computational thinking processes in a real-world scenario. The final project of the program requires teachers to work collaboratively to create a lesson plan or an extended curriculum that incorporates computational thinking in their subject areas.
*Note: Penn GSE Certificates are awarded as a standalone, non-credit bearing education credential.
Our Faculty
Betty Chandy Director for Online Learning, Catalyst @ Penn GSE Ed.D., University of Pennsylvania
Veena Vasudevan Postdoctoral Fellow, American Museum of Natural History Ph.D., University of Pennsylvania
Shamya Karubaiah Doctoral student, University of Pennsylvania
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Our Graduates
The Experiences in Applied Computational Thinking certificate program helps promote:
- Educators who understand the need for computational thinking in the 21st century classroom
- Educators who are comfortable using computational thinking to solve problems and applying computational thinking to real-world scenarios
- Educators who are prepared to incorporate computational thinking into their subject areas
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Computational Thinking for Problem Solving
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program.
This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.
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Computational Thinking for Problem Solving
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Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer.
But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
Interested in what the future will bring? Download our 2024 Technology Trends eBook for free.
In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program. This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.
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Computational Thinking for Problem Solving
This Computational Thinking for Problem Solving offered by Coursera in partnership with University of Pennsylvania will introduce you to people from diverse professions who use computational thinking to solve problems.
![computational thinking for problem solving university of pennsylvania Logo Coursera](https://storage-prtl-co.imgix.net/endor/organisations/17569/logos/sq-17569.png?w=64&auto=format,compress&q=40)
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
The programme
In this Computational Thinking for Problem Solving offered by Coursera in partnership with University of Pennsylvania, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program.
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Programme structure.
Courses include:
- Pillars of Computational Thinking
- Expressing and Analyzing Algorithms
- Operations of a Modern Computer
- Applied Computational Thinking Using Python
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- 17 hours to complete
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Computational Thinking for Problem Solving at Penn
Learn to approach problems systematically with the help of computational thinking skills gained from the Computational Thinking for Problem Solving online cours
Quick Facts
Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
---|---|---|
English | Self Study | Video and Text Based |
Course Overview
Computational Thinking for Problem Solving is a beginner-level course administered by the University of Pennsylvania. The online programme will provide the learners with a deep insight into computational thinking which is used to deal with a problem in a systematic manner and come up with solutions that could be initiated by a computer. Computational Thinking for Problem Solving Certification Syllabus will guide the learners on computation thinking, the development and analysis of algorithms etc that will enable the students to approach the problems from the perspective of computer scientists.
Offered by Coursera , the Computational Thinking for Problem Solving Certification Course is a programme targeted at beginner-level audiences that could be completed within 17 hours. Computational Thinking for Problem Solving Certification by Coursera is developed by Susan Davidson who is the Weiss Professor at the University of Pennsylvania.
The Highlights
- Provided by Coursera
- Approximately 17 hours of programme
- Offered by the University of Pennsylvania
- Flexible Deadlines
- Self-Paced Learning Option
- Shareable Certificate
- Financial Aid Available
- Beginner level course
- 100% Online Course
Programme Offerings
Courses and certificate fees.
Fees Informations | Certificate Availability | Certificate Providing Authority |
---|---|---|
INR | yes | Coursera |
The Computational Thinking for Problem Solving Certification Fee will vary depending on how months the learners want to learn the programme. The fee structure is tabulated below:
|
|
Computational Thinking for Problem Solving | Rs. 2,397 |
Eligibility Criteria
Certification Qualifying Details
The Computational Thinking for Problem Solving Certification will be conferred to the students only if they complete the course proceedings successfully by covering the course readings, videos, assignments and quizzes and paying the Coursera-specified fee.
What you will learn
After the completion of the Computational Thinking for Problem Solving Training, the students will be able to make a thorough understanding of the following:
- Simple Algorithm
- Python Programming
- Problem-Solving
- Computation
Who it is for
Computational Thinking for Problem Solving Classes can be pursued by the professionals such as
- Python Programmer
- Computer Scientist
Admission Details
Step 1- At first, register and sign in on https://www.coursera.org/.
Step 2 - Then, find the course ‘Computational Thinking for Problem Solving’ offered by the University of Pennsylvania will appear on the screen.
Step 3- Kickstart the course by entering the option ‘Enrol’.
The Syllabus
- Introduction
- Decomposition
- Pattern Recognition
- Data Representation and Abstraction
- Case Studies
Practical exercise
- Finding the Largest Value
- Linear Search
- Algorithmic Complexity
- Binary Search
- Brute Force Algorithms
- Greedy Algorithms
- Binary Search1
- A History of the Computer
- Intro to the von Neumann Architecture
- von Neumann Architecture Data
- von Neumann Architecture Control Flow
- Expressing Algorithms in Pseudocode
- Expressing Algorithms in Pseudocode
- Introduction to Python
- Conditional Statements
- Classes and Objects
- Course Conclusion
- Programming on the Coursera Platform
- Python Playground
- Variables Programming Activity
- Solution to Variables Programming Activity
- Conditionals Programming Activity
- Solution to Conditionals Programming Activity
- Solution to Lists Programming Assignment
- Solution to Loops Programming Assignment
- Solution to Functions Programming Assignment
- Solution to Challenge Programming Assignment
- Solution to Classes and Objects Programming Assignment
- Solution to Project Part 4
- Programming Assignment
- Loops Programming Assignment
- Functions Programming Assignment
- (Optional) Challenge Programming Assignment
- Classes and Objects Programming Assignment
- Project Part 4: Implementing the Solution in Python
Instructors
Penn frequently asked questions (faq's).
The University of Pennsylvania is offering the programme.
The course is instructed by Susan Davidson who is the Weiss Professor at Computer & Information Science.
Yes, the subtitle is available in the languages of Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, and Spanish.
Yes, the students can make the payment of the course fee in installments.
No, Coursera does not provide job assistance.
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Computational Thinking for Problem Solving
Description.
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don’t need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program.
This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.
Price: Enroll For Free!
Language: English
Subtitles : English
Computational Thinking for Problem Solving – University of Pennsylvania
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In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python ...
About the Course. Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course.
Computational thinking is a problem-solving process in which the last step is expressing the solution so that it can be executed on a computer. However, before we are able to write a program to implement an algorithm, we must understand what the computer is capable of doing -- in particular, how it executes instructions and how it uses data.
Computational thinking can enhance students' problem-solving skills, empowering them to become confident and successful problem solvers in an increasingly complex world. With this program, educators come to understand computational thinking, re-examine how computational thinking can fit into their current lessons, and become part of a ...
Enroll in Computational Thinking for Problem Solving course here: https://www.coursera.org/learn/computational-thinking-problem-solving
Computational Thinking for Problem Solving. Learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. ... University of Pennsylvania ©2024 ...
University of Pennsylvania via Coursera: Instructors: Susan Davidson, Chris Murphy ... Computational Thinking for Problem Solving is one of the best courses I have taken thus far on Coursera. Read more. computer science in 30 reviews. The professors do an amazing job teaching the fundamentals that can be transferred across all of computer ...
Brute Force Algorithms have Exponential Complexity. Factorial Complexity. Adding one element to Input Size (x-axis) doubles the number of Comparisons (y-axis) by factor of one. Study with Quizlet and memorize flashcards containing terms like Computational Thinking, Four Pillars of Computational Thinking, Decomposition and more.
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Join Now Name: Computational Thinking for Problem Solving Creator: University of Pennsylvania Category: Software > Computer Software > Educational Software Topic: Algorithms, Computer Science Tag: impact, problems, python, scientist, social Availability: In stock Price: USD 49.00
In this Computational Thinking for Problem Solving offered by Coursera in partnership with University of Pennsylvania, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course ...
Computational Thinking for Problem Solving is a beginner-level course administered by the University of Pennsylvania. The online programme will provide the learners with a deep insight into computational thinking which is used to deal with a problem in a systematic manner and come up with solutions that could be initiated by a computer.
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! ... Computational Thinking for Problem Solving - University of Pennsylvania. TUN Helps ...
Computational Thinking for Problem Solving By University of Pennsylvania Educational Resource medium.com Open. Share Add a Comment. Be the first to comment Nobody's responded to this post yet. Add your thoughts and get the conversation going. Top 1% ...
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Computational Thinking for Problem Solving By University of Pennsylvania medium.com Open. Locked post. New comments cannot be posted. Share Add a Comment. Be the first to comment Nobody's responded to this post yet. Add your thoughts and get the conversation going. TOPICS. Gaming. Valheim; Genshin Impact ...