Students interested in a more advanced, optimization-based Lab 09: Regrade requests are due 1 week after grades are released. For questions about homework, course content, package installation, JupyterHub, and after you have tried to troubleshoot yourselves, the process to get help is: 1. Consult the course calendar for exact dates. particular task. Students are encouraged to use Homework Zero [LINK will be added soon] to gauge HW #0 is designed to test your knowledge on the prerequisites. can be accessed through the Course Videos section on Canvas. We will encourage learning that advances ethical data science, exposes bias in the way data science is used, and advances research into fair and responsible data science. If you work with a partner on an assignment make sure both parties solve all the problems. 10 minutes of Q&A regarding the pre-class exercises and/or review of homework and quiz questions. world. Sessions will be accompanied by relevant examples to clarify key concepts and techniques. There will be 9 graded homework assignments. Part I of the textbook Quoting one of our favorite superheroes: with Note for Simultaneous Enrollment: Students considering simultaneous enrollment must note that regular attendance This course is the first half of a oneyear introduction to data science. Data Science and Computer Science have historically been representative of only a small sliver of the population. Each class meeting will consists of. We will focus on the analysis of data to perform predictions using statistical and machine learning methods. Note for Homework 0: Homework 0 will be graded for completion (i.e. NOTE: make sure you adjust your account settings so you can receive emails from Canvas. 25% of the quizzes will be dropped from your grade. We will discuss the motivations behind common machine learning algorithms, and the properties that determine whether or not they will work well for a particular task. You have six late days that can be used for homework CS 181 provides a broad and rigorous introduction to machine learning, Start early and plan ahead! 1. via the Gradescope course website. For more details, check out The CS109A Grade. PDF Course Schedule 2023-24 - music.fas.harvard.edu Free electronic version: http://www-bcf.usc.edu/~gareth/ISL/ (Links to an external site). You will be allowed to bring An Introduction to Statistical Learning by James, Witten, Hastie, Tibshirani. in those gaps. and made available at the beginning of each week. Thus, in addition to the derivations and the practical components, Note: Sections are not held every week. As a student your best guidelines are to be reasonable and fair. If something was said in class (by anyone) that made you feel uncomfortable, please talk to us about it. will only assess your work using the pdf they will not be running your You have the option to work and submit the homework in pairs for all the assignments except two which you will do individually. Successful completion of this assignment will show that this course is suitable for you. Stated most broadly, academic integrity means that all course work submitted, whether a draft or a final version of a paper, project, take-home exam, online exam, computer program, oral presentation, or lab report, must be your own words and ideas, or the sources must be clearly acknowledged. Successful completion of this assignment will show that this course is suitable for you. 2. The material covered in the advanced sections is required for all AC209a students. This will include, reading from the textbooks or other sources, watching videos to prepare you for the class. The course covers a broad range of topics in data science, including data cleaning, visualization, analysis, and machine learning. If you're compliant with the supported viewing requirements but still having trouble, try . Even if you are not a student at Harvard, you are welcome to follow this course for free by working through the course material that are publicly available, If interested in a verified certificate from edX, enroll, If interested in transfer credit and accreditation from. Home | CS181 - GitHub Pages of machine learning methods that can empower you to pursue future theoretical Remember that you can also submit anonymous feedback (which will lead to us making a general announcement to the class, if necessary, to address your concerns). This includes: An Introduction to Statistical Learning by James, Witten, Hastie, Tibshirani. CS 109b: Data Science II: Advanced Topics in Data Science Relatedly, we expect all participants in this course instructors, teaching 3. exploratory data analysis generating hypotheses and building intuition Prior term registration provides an earlier period to . way to handle the situation. Course Website. GitHub - Harvard-IACS/2020-CS109A the site, so submit early enough that you don't accidentally discover that Free electronic version: http://www-bcf.usc.edu/~gareth/ISL/ (Links to an external site). For example, the sections from Tuesday and bonuses for an especially creative or successful approach. You need to attach the note from your medical provider otherwise we will not accept the request. the instructor know in advance of the midterm, get a doctor's note (this We encourage you to talk and discuss the assignments with your fellow students (and on Piazza), but you are not allowed to look at any other students assignment or code outside of your pair. exceptional circumstances. Harvard CS109A | sections - GitHub Pages appropriately adjust). become a problem for you, please let the instructor know, via email, so It is almost always in your interest to turn in partial or Course Instructor Time No. assignments, and includes pointers to other resources we'll use, For students not having access to canvas as yet, HW 0 is cs109a_hw0.ipynb in this folder. 61 pages. Lectures will include one or more coding exercises focused on the newly introduced material; there will be no AC209a content in the exercises. Harvard's CS109A course is an introductory course in data science, designed for students with some prior programming experience. Participating in the Ed discussion forum both through asking thoughtful questions and by answering the questions of others. The quizzes will be available until the next lecture. Team The, exercises are short enough to be completed during the time allotted in lecture, but they will remain available until the beginning of the following lecture to. CS109A - CS109a: Introduction to Data Science - GitHub Pages assignments. CS109a focuses on the analysis of data to perform predictions using statistical and machine learning methods. Due to the volume of the grading, it may not always be possible for For questions about homework, course content, package installation, JupyterHub, and after you have tried to troubleshoot yourselves, the process to get help is: 1. to request extensions beyond late-days. HW0 is designed to test your knowledge on the prerequisites. a practical exercise portion where students work in small teams on a coding or qualitative be submitted in LaTeX and will be returned with grades and solutions. by yourself in your own words. is a concept quiz for you to check your understanding - the quizzes will be graded based on For private matters send an email to the Helpline: cs109a2020@gmail.com. As a student your best guidelines are to be reasonable and fair. assignments to provide a strong and rigorous conceptual grounding in if the assignment allows it you may use third-party libraries and example code, so long as the material is available to all students in the class and you give proper attribution. We will accept late submissions only for medical (if accompanied by a doctor's note) or other official University-excused reasons. 4. prediction or statistical learning As a participant in course discussions, you should also strive to honor the diversity of your classmates. The homework assignments help you practice the core concepts that we The class meets, virtually, three days a week for lectures (M, W, F). Despite being remote and distributed, we want everyone to participate and engage with fellow classmates and staff. address, and all the more so given the continuing pandemic. There will be quizzes at the end of each lecture to assess the understanding of the material that will help us identify gaps. We do not want to see code copied verbatim from the above sources. Throughout the semester, our content continuously centers around five key facets: 1. data collection data wrangling, cleaning, and sampling to get a suitable data set; 2. data management accessing data quickly and reliably; 3. exploratory data analysis generating hypotheses and building intuition; 4. prediction or statistical learning; and. Please note that auditors may not submit assignments for grading or make use of other limited student resources such as office hours. Course Title CS 109 Type Homework Help Uploaded By BrigadierCloverGorilla61 Pages 25 Ratings 100% (3) This preview shows page 1 - 4 out of 25 pages. Gradescope two midterms (15% each, in March and April), The homework are graded on a scale 1 to 5, where 5 is the highest grade. here. Sessions will help students develop the intuition for the core concepts, provide the necessary mathematical background, and provide guidance on technical details. Thus, in CS109A we give a strong emphasis to Academic Honesty. In general, we expect you to use your late days first the whole point The Harvard Law School Library is here for you as you prepare for a new semester! questions, but you must cite your sources (and you should be ready to or other sources (e.g. There will be a midterm exam on October 15th. one sheet of 8.5x11 paper of notes (front and back, any font), and to the To help accomplish this: If you have a name and/or set of pronouns that differ from those in your official Harvard records, please let us know! If you would like to audit the class, please send an email to the Helpline indicating who you are and why you want to audit the class. If still unsatisfied with first regrading outcome, you may submit a reason via email to the Helpline with subject line Regrade HW1: Second request within 2 days of receiving the initial regarding response. Students who have previously taken CS 109, AC 209, or Stat 121 cannot take CS 109a, AC 209a, or Stat 121a for credit. Only one of CS 109a, AC 209a, or Stat 121a can be taken for credit. You will be working in Jupyter Notebooks which you can run in your own environment or in the SEAS JupyterHub cloud. Students will work in groups of 2-4 to complete a final group project, due during the Exams period. Remember, not all assignments will permit group submissions. 2018-CS109A/syllabus.md at master Harvard-IACS/2018-CS109A The Helpline is monitored by TFs. Topics include data scraping, data management, data visualization, regression and classification methods, and deep neural networks. Harvard CS109A | Materials - GitHub Pages There will be 7 graded homework assignments. any students who need to take a midterm at a different time due to Students are expected to watch the relevant If still unhappy with the initial response, then submit a reason via email to the Helpline with subject line "Regrade HW1: Second request" within 2 days of receiving the initial response. It is an honor code violation to AC209a students will have additional homework content for most assignments worth 1 point. CS 109a, AC 209a, Stat 121a, or CSCI E-109a, Pavlos Protopapas (SEAS), Kevin Rader (Statistics), & Chris Tanner (SEAS), Lectures: Mon, Wed, Fri at 9am-10:15am and 3pm-4:15pm, Sections: Fri 1:30-2:45 pm and Mon 8:30-9:45 pm. Standard assignments are graded out of 5 points. Thus, in CS109 we give a strong emphasis to Academic Honesty. Contribute to Harvard-IACS/2018-CS109A development by creating an account on GitHub. Lab sessions are held Thur 4:30-5:45 pm in Pierce 301. Labs are held on Thur 4:30-6:00 pm and Fri 10:30-11:45 am in Pierce 301. or equivalent). applications of machine learning. School Harvard University Course Title CS 109 Uploaded By benpap45801207 Pages 8 This preview shows page 1 - 3 out of 8 pages. Harvard CS109A | FAQ - GitHub Pages and what you send may be seen by the entire course staff. GitHub - Harvard-IACS/2021-CS109B notes available Failure to do so may result in the Course Head's inability to respond in a timely manner. Our course will discuss diversity, inclusion, and ethics in data science. Consult the course calendar for exact dates. If you have an acute illness at the time of a midterm, then you must let The Helpline is monitored by the teaching staff. A tag already exists with the provided branch name. You will submit a pdf of in these times, there is no reason to additionally burden our medical staff but Sessions will help students develop the intuition for the core concepts, provide the necessary mathematical background, and provide guidance on technical details. We respect that there is a learning curve for the material and that students need time to acclimate to the course. Course Description CS 181 provides a broad and rigorous introduction to machine learning, probabilistic reasoning and decision making in uncertain environments. Harvard University - Wikipedia Data Science, like many fields of science, has historically only been represented by a small sliver of the population. We will be holding office hours both in-person and over Zoom (Link will be added soon). still be some bugs, and if you find any please be a good citizen and put If you forgot to join a Group with your peer and are asking for the same grade we will accept this with no penalty up to HW3. and spring course within the same academic year. You can access the notebook viewer either on your own machine by installing the Anaconda platform (Links to an external site) which includes Jupyter/IPython as well all packages that will be required for the course, or by using the SEAS JupyterHub from Canvas. Students will work in groups of 2-4 to complete a final group project, due during the Exams period.

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