UADataLab-workshopsF2023

<img src="https://github.com/clizarraga-UAD7/DataScienceLab/raw/main/images/UADLSquareLogo.png?raw=true" width=150> ::: info # UArizona Data Lab Workshops - Fall 2023 ::: :construction: :construction: :construction: :construction: :construction: *** ::: success > > ## I. Workshop _"Unlocking the Power of Data: A Journey Through Machine Learning & Deep Learning"_ > :bookmark_tabs: [Workshop Wiki](https://github.com/ua-datalab/Workshops/wiki) ::: #### 1. **Introduction to Python for Data Science** **Content**: Basics of Python, variable types, flow control, and functions. [Notes for the Workshop](https://github.com/ua-datalab/Workshops/wiki/Introduction-to-Python-for-Data-Science) / [Link to Zoom recording](https://arizona.zoom.us/rec/share/4oHvg2ZVv2oE4axy8AfKIrq0hsGw6I4KyClOcOWXZsT_Id8w8S0Ko4Ufw4NRTA3c.wjBE_f6PBcS52aoA) - (10-03-2023) **More references:** * [Introduction to Python for Data Science - RezBaz AZ 2022.](https://github.com/clizarraga-UAD7/Workshops/wiki/Introduction-to-Python-for-Data-Science) * [Jupyter Notebooks](https://github.com/clizarraga-UAD7/Workshops/wiki/Jupyter-Notebooks) #### 2. **Data Wrangling 101: Pandas in Action** **Content**: Data manipulation and cleaning using Pandas. [Notes for the Workshop](https://github.com/ua-datalab/Workshops/wiki/Pandas-for-Data-Analysis) / [Link to Zoom recording](https://arizona.zoom.us/rec/share/qJroJ0ZpGJrx7COBBE4Vkw5EuVYs0l7q0X3i1ZFaG3WY67KBPMsADHb1ulZMcew-.zeCTYDwRtFSSxl7l) (10-10-2023) **More references**: * [Pandas for Data Analysis](https://github.com/clizarraga-UAD7/Workshops/wiki/Pandas-for-Data-Analysis) * [Exploratory Data Analysis with Python](https://github.com/clizarraga-UAD7/Workshops/wiki/Exploratory-Data-Analysis) #### 3. **Statistical Inference: The Backbone of Data Science** **Content**: Descriptive and inferential statistics. [Notes for the Workshop](https://github.com/ua-datalab/Workshops/wiki/Statistical-Inference) / [Link to Zoom recording](https://arizona.zoom.us/rec/share/-3hPUfIlDHmm-TvZk2oxk-EYrafTu5zA4yqL5lP0nl8vcp1NddussAQXOMKTyjlI.943CeiYkK2GM7Y0n?startTime=1697573332000) (10-10-2023) **References**: #### 4. **Machine Learning Basics: Scikit-learn Unveiled** **Content**: Introduction to machine learning libraries in Python. [Notes](https://github.com/ua-datalab/Workshops/wiki/Machine-Learning-Basics:-scikit%E2%80%90learn-Unveiled) | [Link to Zoom recording](https://arizona.zoom.us/rec/share/0tgbnzZ0KTcVAAlXVfoC8_6R_s46NFKZhfj-B0J9IZ9CzYuIldUi-2Jy-tyCeokz.7o2COrWoKayYv5Nk?startTime=1698178193000) **References**: * [Introduction to Machine Learning](https://github.com/clizarraga-UAD7/Workshops/wiki/Introduction-to-Machine-Learning) * [Overview of Machine Learning Algorithms](https://github.com/clizarraga-UAD7/Workshops/wiki/An-Overview-of-Machine-Learning-Algorithms) #### 5. **Natural Language Processing: Text Mining and Sentiment Analysis** **Content**: Text data processing and sentiment analysis. [Notes](https://github.com/ua-datalab/Workshops/wiki/Natural-Language-Processing:-Text-Mining-and-Sentiment-Analysis) | [Link to Zoom recording](https://arizona.zoom.us/rec/share/zPdhHe4f2QiMp2gUQ_SG-4keC8bEolyV3H9G8DqKR8c2kirfurN3mO78SIk2VFg.uCpUPVEGNDU3U1rF?startTime=1698784397000). #### 6. **Time Series Analysis: Forecasting the Future** [Notes](https://github.com/ua-datalab/Workshops/wiki/Time-Series-Analysis) | [Link to Zoom recording](https://arizona.zoom.us/rec/share/JQD1XHWBSGT2T9pZ5P7J0nx6aTmeYtmYBL1bx4HzdF-JU8lGq3rrMzQBHqP6YP8t.hZiVPmXo0ciYztbs?startTime=1699386144000) (11-0-2023) **Content**: Time series data analysis and forecasting techniques. **References**: #### 7. **Deep Dive into Deep Learning: Neural Networks Demystified** **Content**: Introduction to neural networks and deep learning. **References**: * UT Austin's AI and Machine Learning Program[**[4](https://onlineexeced.mccombs.utexas.edu/online-ai-machine-learning-course)**]. * [Overview of Deep Learning Algorithms](https://github.com/clizarraga-UAD7/Workshops/wiki/Overview-of-Deep-Learning-Algorithms) #### 8. **Computer Vision: Image and Video Analysis** **Content**: Basics of image and video data processing. :spiral_note_pad: [Notes](https://github.com/ua-datalab/Workshops/wiki/Computer-Vision:-Image-Analysis) :video_camera: [Zoom recording link](https://arizona.zoom.us/rec/share/VkHK0o4bKb7oVFLYlDlDUbrz1USEOfvAZBt3tCv27AEIH7GhGQ4vq7GqOTqlsRA7._ypokB-dKD4SEOGq?startTime=1700595291000) **References**: * *** ::: info >#### Tuesday's Workshop: "Unlocking the Power of Data: A Journey Through Machine Learning & Deep Learning" > > **Room:** **_Main Library: Catalyst Data Studio_** > | Date | Time | Title | | :--: | :--: | :-- | | 10/03 | 1pm | Introduction to Python for Data Science (Megh) | | 10/10 | 1pm | Data Wrangling 101: Pandas in Action (Brenda) | | 10/17 | 1pm | Statistical Inference: The Backbone of Data Science (Carlos) | | 10/24 | 1pm | Machine Learning Basics: Scikit-learn Unveiled (Carlos) | | 10/31 | **2pm** | Natural Language Processing: Text Mining and Sentiment Analysis (Megh) | | 11/07 | 1pm | Time Series Analysis: Forecasting the Future (Shravan) | | 11/14 | 1pm | Deep Dive into Deep Learning: Neural Networks Demystified (Mithun) | | 11/21 | 1pm | Computer Vision: Image Analysis (Michele, Brenda)| | 11/28 | 1pm | AI Tools Landscape (Carlos) | ::: *** ::: success > > ## II. Workshop _"Introduction to Deep Learning"_ > :bookmark_tabs: [Workshop Wiki](https://github.com/ua-datalab/DLWorkshops/wiki) ::: #### 1. Deep Learning Refresher (Mithun) [Notes for the Workshop](https://github.com/ua-datalab/DLWorkshops/wiki/Lecture1:-Introduction-To-HuggingFace) / [Zoom recording](https://arizona.zoom.us/rec/share/RhxfiuurCmetpBgPcxdPUvj73G5PuVu8dY5Q_vSWPaYyUB2_iAINWSuWd07toWAp.4p1kq-cFAdh46hTp?startTime=1697141373000) | [Part 2](https://arizona.zoom.us/rec/share/GTRm53SPXDGBbj8ooUcAzGvvtt7ojOoQch3asuK6VNBsE3Dq0lyz0qRp4nIYuAZZ.34dqJmomIn6tUGb7?startTime=1697141480000) (10-12-2023) - **Reference**: - What are neural networks? - Encoders - Decoders - Sequence to Sequence #### 2. **Introduction to HuggingFace** :notebook: [Materials](https://github.com/ua-datalab/DLWorkshops/wiki/Lecture2:-Introduction-To-Transformers) | :movie_camera: [Zoom recording](https://arizona.zoom.us/rec/share/UWCpupRr_SpWc9If4HIQxwKgJVd3OjMQMijiVM3CMelpf2qjHrZIROQvil33DsDI.9waXaWGlGkIb8x_s?startTime=1697746026000) - **Reference**: [HuggingFace](https://huggingface.co/) . #### 3. **Fine-tuning a pre-trained model** :notebook: [Materials](https://github.com/ua-datalab/DLWorkshops/wiki/Lecture3:-Fine-Tuning-A-Pre-trained-Model) | :movie_camera: [Zoom recording](https://arizona.zoom.us/rec/share/_psFkKSU27oDU4-BvkfNq2z6oOfyYNgKdX5dp3zooQ8ZLExV5cGDoiLeHTgDOgsP.zmWxx8aDkJTl5I8r?startTime=1698349763000) - **Reference**: TBD #### 4. How GPT and other Large Language Models Work :notebook: [Materials](https://github.com/ua-datalab/DLWorkshops/wiki/Lecture4:-Introduction-to-ChatGPT) :movie_camera: [Zoom recordings link](https://arizona.zoom.us/rec/share/l3OZeaIno_G2esLO-mfJkghiCBi1t449dtVWy02ZbvmZSZT6UH8moInfjXXqYeYg.HCBVXMMPNO_aGHPt?startTime=1698954890000) - **Reference**: TBD #### 5. **Training a model from scratch** [Zoom recording link](https://arizona.zoom.us/rec/share/CHa_GacX12C-iMSSHRxEXA6HFsBZl33K-f9ttVzmh9tdkNwp4oi7CcgxtwVNMhIv.DhG8MRUD7IBw8IA7?startTime=1699558919000) - **Reference**: TBD #### 6. **Databricks and SageMaker** - **Reference**: TBD #### 7. **How GPT and other Large Language Models Work** - **Reference**: TBD Open topics/possible additions - Multimodality - Generative models - Bard, LLAMA, AI Image generators, DALL-E. *** ::: info > #### Thursday's Workshop: "Intro to Deep Learning: An Exploration" > >**Room:** **_Weaver Science and Engineering Library 212_** | Date | Time | Title | | :--: | :--: | :-- | | 10/12 | 1pm | Intro to hugging face | | 10/19| 1pm | Using Transformers | 10/26 | 1pm | Fine Tuning A Pre-trained model| | 11/02 | 1pm |How GPT and other Large Language Models Work X | 11/09 | 1pm | Fine tuning GPT | 11/16 | 1pm |Fast.AI, spacy.io , Databricks, SageMaker, Cyverse| | 11/23 | - | Thanksgiving Day | | 11/30 | 1pm |Reinforcement learning, Multimodal- vision, video, audio, Quantum AI| ::: *** ::: success > >## III. Workshop _"Mastering High-Performance Computing and Machine Learning"_ > ::: #### 1. Navigating Campus HPC for Machine Learning Projects - **Main Content**: Introduction to campus High-Performance Computing (HPC) resources, setting up accounts, and running basic machine learning algorithms. - **Factual Example**: Middle school students collaborating with practicing scientists over the Internet can benefit from HPC resources for data-intensive tasks[[3](https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf)]. #### 2. Optimizing ML and DL Workloads on Campus HPC - **Main Content**: Best practices for distributing machine learning and deep learning tasks across HPC clusters. - **Factual Example**: Workshops can introduce practical skills and techniques for optimizing workloads[[2](https://ctb.ku.edu/en/table-of-contents/structure/training-and-technical-assistance/workshops/main)]. #### 3. GPU Utilization for Accelerated Computing - **Main Content**: Overview of Graphics Processing Units (GPUs), and how to effectively use them for computational tasks. - **Factual Example**: Determining the main idea or topic is crucial for effective GPU utilization[[6](https://www.oecd.org/education/school/programmeforinternationalstudentassessmentpisa/33693997.pdf)]. #### 4. Crafting Your Ideal Programming Environment - **Main Content**: Setting up IDEs, version control, and containerization for a seamless programming experience. - **Factual Example**: Academic Essay Writing for Postgraduates discusses planning, drafting, and revising assignments, similar to setting up a programming environment[[5](https://www.ed.ac.uk/files/atoms/files/aewpg_ismaterials.pdf)]. #### 5. Leveraging Hugging Face for Deep Learning - **Main Content**: Introduction to the Hugging Face library, and how to implement transformers for NLP tasks. - **Factual Example**: Trained and skilled volunteers can be valuable assets in implementing deep learning projects[[1](https://www.samhsa.gov/sites/default/files/volunteer_handbook.pdf)]. #### 6. Mastering PyTorch and PyTorch Lightning - **Main Content**: Introduction to PyTorch and PyTorch Lightning frameworks, and how to build and deploy models. - **Factual Example**: Research-based frameworks can help leaders understand six types of family and community involvement, similar to understanding machine learning frameworks[[4](https://www.govinfo.gov/content/pkg/ERIC-ED467082/pdf/ERIC-ED467082.pdf)]. #### 7. Data Pipelines #### 8. ... *** ::: info > >#### Wednesday's Workshop: "Mastering High-Performance Computing and Machine Learning " > >**Room:** **TBD** | Date | Time | Title | | :--: | :--: | :-- | | | | Navigating Campus HPC for Machine Learning Projects | | | | Optimizing ML and DL Workloads on Campus HPC | | | | GPU Utilization for Accelerated Computing | | | | Crafting Your Ideal Programming Environment | | | | Leveraging Hugging Face for Deep Learning | | | | Mastering PyTorch and PyTorch Lightning | | | | TBD | | | | TBD | ::: *** ::: success > > **[IV UArizona DataLab](https://www.datascience.arizona.edu/research/uarizona-data-lab)** *A SQL Masterclass: Research & Interview Focused Workshop* > ::: Become an SQL knowledgeable with our two-part sessions. Part 1, covers basic topics such as tables, joins, filtering, and views. Part 2, explores advanced techniques like subqueries, CTEs, and window functions. **Learning Objectives**: Master the fundamentals of SQL and advanced techniques. Learn how to integrate data using joins and views. Handle unstructured data effortlessly. Impress in interviews with your advanced SQL skills. **Instructors:** Ankit Pal & Carlos Lizárraga **When:** Monday Oct. 16th. 1 PM **Where:** Virtual **[Please register](https://uarizona.co1.qualtrics.com/jfe/form/SV_7Ut5xZmKF67a3Qi)** now for an amazing SQL learning experience, and attend the [virtual Zoom session](https://arizona.zoom.us/j/84309105282). **SQL workshop** [Zoom recording](https://arizona.zoom.us/rec/share/fZuRxoPuXcQRq5D078bveqhj6pm9XZRnUdxWzvd1ggR8aM9EOmiebt9ydpX7e63y.czKbtAqIHPZZEnqz?startTime=1697486674000) | [Jupyter Notebook](https://github.com/ua-datalab/Workshops/blob/main/A_SQL_Masterclass/A_SQL_Masterclass_Part_1_.ipynb) (10-16-2023) *** Updated: 09/26/2023 Carlos Lizárraga UArizona Data Lab @ Data Science Institute

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