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This work proposes a systematic approach to teaching the latest developments in a cohesive, consistent way: systematically consuming the literature, summarizing and standardizing it, implementing working examples, and presenting topics clearly. It reports author best practices from a decade of teaching, including course structure, lecture construction stages, and practical workflows for slides, implementation, and student evaluation.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/teaching-deep-learning-course-curriculum-creation-and-lecture-development-best-practices/657531/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/teaching-deep-learning-course-curriculum-creation-and-lecture-development-best-practices/657531.png","ImageObject",300,407,{"name":92,"@type":93},"Quinn Holloway","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-10-26",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What teaching approach does the paper propose for deep learning topics?","Question",{"text":112,"@type":113},"It proposes systematically consuming current literature, summarizing and standardizing it, implementing working examples, and delivering concise, consistent presentations.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How is the 14-week course structured in the curriculum section?",{"text":117,"@type":113},"The course is planned as a 14-week semester with weekly theory and practical sessions, then sliced into 2-week thematic units, and partitioned into foundational and more advanced halves.",{"name":119,"@type":110,"acceptedAnswer":120},"What are the stages for creating a single lecture?",{"text":121,"@type":113},"The lecture creation process is described in three stages: literature review, numerical implementation, and crafting the slides.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},657531,1792982320,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":24,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":143},2336474466712,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Teaching Deep Learning, a boisterous ever-evolving field  \nAlfredo Canziani 1  \nAbstract  \nMachine and deep learning techniques are actively being developed with over 150 papers submitted daily to arXiv, each of which is introducing its own notation. To offer a course that reflectsthe latest developments of the field and illustrate them in a cohesive and consistent manner, one needs to systematically consume the literature, summarise and standardise it, implement working examples, and deliver a concise and consistent presentation of a given topic. This paper reports all the best practices developed by the author in his last decade of teaching experience.  \n1. Course curriculum creation  \nWe shall consider the creation of a 14-week course, standard length for a single semester at my institution, comprising a 2-hour theory and 1-hour practical session a week.  \nIt has proven effective to slice the content into smaller twoweek-long units sharing a common theme, as shown in fig. 1. Not only do they provide a sense of uniformity, purpose, and clarity across the lessons, but they also help the student feel motivated and give them a sense of achievement when a given theme is completed.  \nIn addition, the course is partitioned into two halves, 3 􀀂 2-week foundational themes (with one or two additional weeks before the mid-term exam), and the remainder more advanced topics, often delivered by experts of the field, with the students focussing on the final Kaggle-like competition (Masters' students) or research project (PhD students) . Holding a competition has proven very effective for evaluating the students uniformly by comparing their final scoreson a given task. It also allows us to assess their ability to source relevant literature, open-source code, and techniques to maximise the final performance.  \nFinally, for each foundational theme in the first half of the semester, homework is assigned to have the students exten-  \n1Courant Institute of Mathematical Sciences, New York University. Correspondence to: Alfredo Canziani \u003C[canziani@nyu.edu](canziani@nyu.edu) >.  \nProceedings of the 2 nd Teaching in Machine Learning Workshop, PMLR, 2021 . Copyright 2021 by the author(s) .  \n1 week mid semester  mid-term exam span  \n\n| P1 | P2 | P3 | P4 | P\\#: paper |  |  |  | P1 | P2 | P3 | P4 | PowerPoint |  |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| literature r |  |  |  | eview and sum |  |  |  | marisation |  |  |  | implementation | slides creation |\n|  |  |  |  | P1 | P2 | P3 | P4 | Jupyter Notebook |  |  |  |  |  |\n\n1 day  \nFigure 1 . Semester (top) and week (bottom) partitioning. Top: each week comprises a 2 hour theoretical (T) and a 1 hour practical (P) session. Lessons are grouped in 2-week thematic blocks in the first half of the semester. Bottom: for a 3 day period, one may read and summarise 4 papers each day, use one day for the numerical implementation, and the remaining day for crafting the slides.  \nsively familiarise themselves with both mathematical and programming notions. Such assignments are intended tobe intensive, geared toward students who are new to coding or need to review the fundamentals of linear algebra, calculus, or probability. Machine and deep learning papers and source codes publicly available demand fluency in both skills, which can be acquired only through exhaustive diligent practice.  \n2. Creating a single lecture  \nThe process behind the creation of a single lecture has multiple stages: (1) literature review [3 days, 4 papers a day];  \n(2) numerical implementation [1 day]; (3) deck slides creation [1 day] . This time allocation is shown in fig. 1.  \n2.1. Literature review  \nWe shall assume we lack specific knowledge of a given novel topic (not yet covered in textbooks) and need to read the literature to learn about the details. It is usually sufficient to cover a dozen papers, starting with the “original” one and following with the most cited follow-ups found by using website","cbCaingEz7JtiJRy","https://ap.wps.com/l/cbCaingEz7JtiJRy","pdf",760768,"English","# Abstract\n# Course curriculum creation\n## Creating a 14-week course structure\n## Creating a single lecture\n### Literature review\n### Numerical implementation\n### Crafting the slides","[{\"question\":\"What teaching approach does the paper propose for deep learning topics?\",\"answer\":\"It proposes systematically consuming current literature, summarizing and standardizing it, implementing working examples, and delivering concise, consistent presentations.\"},{\"question\":\"How is the 14-week course structured in the curriculum section?\",\"answer\":\"The course is planned as a 14-week semester with weekly theory and practical sessions, then sliced into 2-week thematic units, and partitioned into foundational and more advanced halves.\"},{\"question\":\"What are the stages for creating a single lecture?\",\"answer\":\"The lecture creation process is described in three stages: literature review, numerical implementation, and crafting the slides.\"}]","Teaching Deep Learning - Course Curriculum Creation and Lecture Development Best Practices | PDF",13]