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Miscellaneous tasks. Adding in Issue Templates and Pull Request Templates so that participants have access to them when repo is forked. Adding vscode to the gitignore file. Added a standardized submissions heading to all assignments. Updating links in README.md to reflect new changes. Changing "data structures and algorithms" to "algorithms and data structure" as to reflect the actual name of the module. Removing Contributions and only leaving land acknowledgements.
Copy file name to clipboardexpand all lines: 02_assignments/assignment_1.ipynb
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Submission Requirements\n",
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"\n",
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"Create and submit a public GitHub repository with the following:\n",
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"\n",
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"- The PDF of the problem you have solved\n",
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"\n",
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"## Evaluation Criteria\n",
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"\n",
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"- Problem is accurately stated in the student’s own words\n",
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"\n",
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"- Clarity in explaining why the solution works, its time and space complexity\n",
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"\n",
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"- Clarity in the proposal to the alternative solution\n",
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"- Clarity in the proposal to the alternative solution"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Submission Information\n",
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"\n",
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"Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md) for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.\n",
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"\n",
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"### Submission Parameters:\n",
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"* Submission Due Date: `HH:MM AM/PM - DD/MM/YYYY`\n",
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"* The branch name for your repo should be: `assignment-1`\n",
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"* What to submit for this assignment:\n",
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" * This Jupyter Notebook (assignment_1.ipynb) should be populated and should be the only change in your pull request.\n",
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"* How the pull request link should look like for this assignment: `https://github.com/<your_github_username>/algorithms_and_data_structures/pull/<pr_id>`\n",
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" * Please verify that this link format is correctly implemented and accessible in a private browser session. This ensures that the technical facilitator and learning support staff can access your submission without any issues.\n",
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"\n",
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"Checklist:\n",
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"- [ ] Created a branch with the correct naming convention.\n",
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"- [ ] Ensured that the repository is public.\n",
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"- [ ] Reviewed the PR description guidelines and adhered to them.\n",
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"- [ ] Verified that the pull request link is correctly formatted and accessible via a private browser session.\n",
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"\n",
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"## Submission Deadline\n",
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"TBD\n"
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"If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via Slack or email. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges."
Copy file name to clipboardexpand all lines: 02_assignments/assignment_2.ipynb
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"# Your answer here"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"## Submission Requirements \n",
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"\n",
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"In the same repository you submitted assignment 1, please ADD the following:\n",
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"\n",
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"- The PDF of the Jupyter Notebook you created for Assignment 2.\n",
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"\n",
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"Please name your files appropriately!\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"\n",
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"- Clarity in explaining why the solution works, its time and space complexity\n",
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"\n",
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"- Quality of critique of your partner's assignment, if necessary\n",
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"- Quality of critique of your partner's assignment, if necessary\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Submission Information\n",
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"\n",
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"Please review our [Assignment Submission Guide](https://github.com/UofT-DSI/onboarding/blob/main/onboarding_documents/submissions.md) for detailed instructions on how to format, branch, and submit your work. Following these guidelines is crucial for your submissions to be evaluated correctly.\n",
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"\n",
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"### Submission Parameters:\n",
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"* Submission Due Date: `HH:MM AM/PM - DD/MM/YYYY`\n",
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"* The branch name for your repo should be: `assignment-2`\n",
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"* What to submit for this assignment:\n",
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" * This Jupyter Notebook (assignment_2.ipynb) should be populated and should be the only change in your pull request.\n",
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"* How the pull request link should look like for this assignment: `https://github.com/<your_github_username>/algorithms_and_data_structures/pull/<pr_id>`\n",
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" * Please verify that this link format is correctly implemented and accessible in a private browser session. This ensures that the technical facilitator and learning support staff can access your submission without any issues.\n",
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"\n",
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"## Submission Deadline\n",
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"Checklist:\n",
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"- [ ] Created a branch with the correct naming convention.\n",
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"- [ ] Ensured that the repository is public.\n",
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"- [ ] Reviewed the PR description guidelines and adhered to them.\n",
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"- [ ] Verified that the pull request link is correctly formatted and accessible via a private browser session.\n",
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"\n",
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"TBD\n"
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"If you encounter any difficulties or have questions, please don't hesitate to reach out to our team via Slack or email. Our Technical Facilitators and Learning Support staff are here to help you navigate any challenges.\n"
| 1 | Motivation and Big-O Notation |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/lessons/1_motivation-big-o.pdf)|
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| 2 | Data Structures, Sorting, and Searching |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/lessons/2_ds-search-sort.pdf)|
| 1 | Motivation and Big-O Notation |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/01_slides/1_motivation_big_o.ipynb)|
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| 2 | Data Structures, Sorting, and Searching |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/01_slides/2_ds_search_sort.ipynb)|
| 5 | Recursive Data Structures |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/01_slides/3_recursion.ipynb)|
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## How do you assign assignments?
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Assignments are given and assigned at the start of each week at the end of the first lecture. The Technical Facilitator will announce to the learners what the assignment is about, and how everything they will learn within the week will equip them to work on the assignment.
Copy file name to clipboardexpand all lines: README.md
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+[Videos](#videos)
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+[How to get help](#how-to-get-help)
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*[Folder Structure](#folder-structure)
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*[Acknowledgements and Contributions](#acknowledgements-and-contributions)
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*[Achnowledgements](#achnowledgements)
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+[Contributions ](#contributions)
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*[Acknowledgement](#acknowledgement)
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## Description
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The course was created by the University of Toronto's Data Science Institute. An understanding of data structures and algorithms (DSA), will aid the implementation of data science or machine learning methods in practice. Machine learning emphasizes prediction, scalability, and autonomy. Understanding DSA is essential to the latter two aims of ML. For instance, students will be able to describe how algorithms will perform when scaled or find practical methods for computers to solve problems autonomously. Finally, the industry often requires knowledge of DSAs and the ability to communicate the solving process. This course will provide the knowledge and terminology necessary to succeed in these situations.
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The course was created by the University of Toronto's Data Science Institute. An understanding of algorithms and data structures will aid the implementation of data science or machine learning methods in practice. Machine learning emphasizes prediction, scalability, and autonomy. Understanding DSA is essential to the latter two aims of ML. For instance, students will be able to describe how algorithms will perform when scaled or find practical methods for computers to solve problems autonomously. Finally, the industry often requires knowledge of DSAs and the ability to communicate the solving process. This course will provide the knowledge and terminology necessary to succeed in these situations.
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The beginning of the course will introduce students to terminology to discuss algorithms. This includes Big-O notation, time and space complexity. The next section will explore array-based data structures, searching, and sorting. Students should be able to justify algorithm or data structure choices based on time and space complexity analysis. Then, students will be introduced to recursion. We will solve problems using recursion and implement data structures that are best understood from a recursive perspective. Again, students will justify their design choices. The last portion of the course will be dedicated to solving optimization problems quickly. Students will be introduced to a variety of techniques to solve problems and identify when and how a solution can be optimized.
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* Learners must not use generative AI such as ChatGPT to generate code to complete assignments. It should be used as a supportive tool to seek out answers to questions you may have.
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* We expect learners to have completed the [onboarding repo](https://github.com/UofT-DSI/Onboarding/tree/tech-onboarding-docs).
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* We expect learners to have completed the [onboarding repo](https://github.com/UofT-DSI/onboarding/tree/main/onboarding_documents).
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* Webcam is optional although highly encouraged. We understand that not everyone may have the space at home to have the camera on.
| 1 | Motivation and Big-O Notation |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/lessons/1_motivation-big-o.pdf)|
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| 2 | Data Structures, Sorting, and Searching |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/lessons/2_ds-search-sort.pdf)|
| 5 | Recursive Data Structures |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/lessons/4_recursive-ds.pdf)|
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| 1 | Motivation and Big-O Notation |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/01_slides/1_motivation_big_o.ipynb)|
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| 2 | Data Structures, Sorting, and Searching |[Slides](https://github.com/UofT-DSI/algorithms_and_data_structures/blob/main/01_slides/2_ds_search_sort.ipynb)|
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* README: This file!
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* .gitignore: Files to exclude from this folder, specified by the Technical Facilitator
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## Acknowledgements and Contributions
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## Acknowledgement
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We wish to acknowledge this land on which the University of Toronto operates. For thousands of years, it has been the traditional land of the Huron-Wendat, the Seneca, and most recently, the Mississaugas of the Credit River. Today, this meeting place is still the home to many Indigenous people from across Turtle Island and we are grateful to have the opportunity to work on this land.
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### Achnowledgements
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* The module was developed by [Alex](https://www.linkedin.com/in/kunzhi-yu/) Yu](https://www.linkedin.com/in/kunzhi-yu/) under the supervision of Rohan Alexander.
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* We wish to acknowledge this land on which the University of Toronto operates. For thousands of years, it has been the traditional land of the Huron-Wendat, the Seneca, and most recently, the Mississaugas of the Credit River. Today, this meeting place is still the home to many Indigenous people from across Turtle Island and we are grateful to have the opportunity to work on this land.
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### Contributions
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*`algorithms_and_data_structures` welcomes issues, enhancement requests, and other contributions. To submit an issue, use the [GitHub
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