└── README.md /README.md: -------------------------------------------------------------------------------- 1 | ## The Breaking Into Data Handbook 2 | 3 | In this repo you will find valuable resources to get you started in 4 | Data Analytics, Data Science, Data Engineering, Machine Learning and Computer Science. 5 | 6 | **This is an open-source effort.** 7 | Please add any links you have found helpful with PR! 8 | 9 | **P.S. Don't be overwhelmed.** 10 | Find what works for you. 11 | And stick to it every day! 12 | 13 | Here you will find: 14 | 15 | - Courses 16 | - Books 17 | - Communities 18 | - Hackathons 19 | - Projects 20 | - Content Creators to follow 21 | - Podcasts 22 | - Newsletters 23 | 24 | --- 25 | 26 | ## Courses: 27 | 28 | Free: 29 | 30 | [Kaggle Courses](https://www.kaggle.com/learn) 31 | [Deep Learning with Fast AI](https://www.fast.ai/)\ 32 | [Leetcode Challenges](https://leetcode.com/) 33 | [Weights and Biases deployment](https://www.wandb.courses/collections) 34 | [Langchain LLM development](https://python.langchain.com/docs/additional_resources/tutorials) 35 | [Harvard Online Data Science Courses](https://pll.harvard.edu/catalog?topics%5B714%5D=714&price%5B1%5D=1&max_price=&start_date=&modality%5BOnline%5D=Online&keywords=) 36 | [Coursera Data Science Courses](https://www.coursera.org/courses?query=free%20courses%20data%20science) 37 | [Alex Freberg's Data Analyst Boot Camp](https://www.youtube.com/watch?v=rGx1QNdYzvs)\ 38 | [Python for Everybody](https://www.py4e.com/) 39 | 40 | Paid: 41 | 42 | [Analyst Builder](https://www.analystbuilder.com) 43 | [Codecademy](https://www.codecademy.com/) 44 | [Data Camp](https://www.datacamp.com/) 45 | [Data With Danny](https://www.datawithdanny.com/) 46 | 47 | ## Books 48 | 49 | [Ace The Data Science Interview](https://www.amazon.com/Ace-Data-Science-Interview-Questions/dp/0578973839/ref=sr_1_1?crid=DUMNXSRM8WZA&keywords=data+science+books+ace+interview&qid=1701977838&s=audible&sprefix=data+science+books+ace+interbie%2Caudible%2C146&sr=1-1-catcorr) 50 | [Building a Second Brain - Excellent guide for Productivity](https://www.amazon.com/Building-Second-Brain-Organize-Potential/dp/B09MGFGV3J/ref=sr_1_1?crid=B3BH2B79FE51&keywords=second+brain&qid=1701975182&sprefix=second+brai%2Caps%2C181&sr=8-1) 51 | [Data Engineering Fundamentals by Joe Reis & Matt Housley](https://www.amazon.com/Fundamentals-Data-Engineering-Robust-Systems/dp/B0CN1SDG2S/ref=sr_1_2?crid=3JOLANS38MVA5&keywords=data+science+fundamentals&qid=1701977884&s=audible&sprefix=data+science+fundamental%2Caudible%2C138&sr=1-2) 52 | [Designing Machine Learning Systems by Chip Huyen](https://www.amazon.com/Designing-Machine-Learning-Systems-Production-Ready/dp/1098107969/ref=sr_1_1?crid=V44JMHSBD5KD&keywords=machine+learning+fundamentals+chip&qid=1701975138&sprefix=machine+learning+fundamentals+chip%2Caps%2C191&sr=8-1) 53 | [Naked Statistics](https://www.amazon.com/Naked-Statistics-Charles-Wheelan-audiobook/dp/B00CH7FWWU/ref=sr_1_1?crid=1PZOQ6DG4HKYP&keywords=naked+statistics&qid=1701978733&sprefix=naked+statistic%2Caps%2C168&sr=8-1) 54 | [Automate the Boring Stuff with Python (Free!)](https://automatetheboringstuff.com/) 55 | [The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition](https://a.co/d/gmJBHOD) 56 | [Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems](https://a.co/d/iSm9331) 57 | [Learning Spark, Second Edition](https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf) 58 | 59 | ## Communities 60 | 61 | [Break Into Data](https://discord.gg/HQ3E44uA2f) 62 | [Cohere Community](https://discord.gg/co-mmunity) 63 | [Roboflow Universe Community for Computer Vision ML](https://universe.roboflow.com/) 64 | [Chip Huyen's MLOps Community](https://discord.gg/dzh728c5t3) 65 | [DataTalks Club](https://datatalks.club/slack) 66 | [AICamp](https://www.aicamp.ai/) 67 | 68 | ## Hackathons 69 | 70 | [Hackathons hosted by Lablab](https://lablab.ai) 71 | [DevPost Hackathons](https://devpost.com/hackathons) 72 | 73 | ## Free Projects 74 | 75 | [Kaggle Datasets](https://www.kaggle.com/datasets) 76 | [Project Pro](https://www.projectpro.io/projects/data-science-projects) 77 | [Data Camp Projects](https://www.datacamp.com/projects) 78 | 79 | ## Content Creators : 80 | 81 | ### Linkedin : 82 | 83 | [Meri Nova - Data Science](https://www.linkedin.com/in/meri-bozulanova/) 84 | [Daliana Liu - Data Science](https://www.linkedin.com/in/dalianaliu/) 85 | [Alex Freberg - Data Analytics](https://www.linkedin.com/in/alex-freberg) 86 | [Jess Ramos - Data Analytics](https://www.linkedin.com/in/jessramosmsba/) 87 | [Megan Lieu - Data Analytics](https://www.linkedin.com/in/meganlieu/) 88 | [Danny Ma - SQL](https://www.linkedin.com/in/datawithdanny/) 89 | [Vin Vashishta - AI](https://www.linkedin.com/in/vineetvashishta/) 90 | [Nick Singh - SQL & Interviews](https://www.linkedin.com/in/nick-singh-tech/) 91 | [Sundas Khalid - Data Science](https://www.linkedin.com/in/sundaskhalid/) 92 | 93 | ### Youtube: 94 | 95 | [Alex the Analyst](https://www.youtube.com/@AlexTheAnalyst) 96 | [Charlotte Fraza - Computational Neuroscience](https://www.youtube.com/@CharlotteFraza) 97 | [ByteByteGo System Design](https://www.youtube.com/@ByteByteGo) 98 | [Ken Jee](https://www.youtube.com/@KenJee_ds) 99 | [Tina Huang](https://www.youtube.com/@TinaHuang1) 100 | [StatQuest by Josh Starmer](https://www.youtube.com/@statquest) 101 | 102 | ### Tiktok: 103 | 104 | [Alex Freberg](https://www.tiktok.com/@Alex_theanalyst) 105 | [Charlotte Chaze](https://www.tiktok.com/@charlottechaze) 106 | 107 | ### Twitter 108 | 109 | [Meri Nova](https://twitter.com/intelligentle__)\ 110 | [Alex Freberg](https://www.twitter.com/Alex_TheAnalyst) 111 | [Daliana Liu](https://www.twitter.com/DalianaLiu) 112 | [Vin Vashista](https://twitter.com/v_vashishta) 113 | [Nick Singh](https://twitter.com/NickSinghTech) 114 | 115 | ## Podcasts 116 | 117 | [Gradient Dissent by W&B](https://wandb.ai/fully-connected/podcast) 118 | [DataFramed Podcast](https://www.datacamp.com/podcast) 119 | [Towards Data Science Podcast](https://towardsdatascience.com/podcast/home) 120 | [Practical AI](https://changelog.com/practicalai) 121 | [Chai Time Data Science](https://sanyambhutani.com/tag/chaitimedatascience/) 122 | [The Data Scientist Show](https://www.youtube.com/@TheDataScientistShow) 123 | [AI Chronicles](https://www.youtube.com/channel/UCVXhvCHU_wZ7lnzal-ZpfMQ) 124 | 125 | ## Newsletters 126 | 127 | [Break Into Data](https://merinova.substack.com/)\ 128 | [Towards Data Science](https://towardsdatascience.com/)\ 129 | [ByteByte Go Newsletter System Design](https://substack.com/@bytebytego) 130 | [Data Analysis Journal by Olga](https://dataanalysis.substack.com/) 131 | [Marvelous Mlops Newsletter](https://marvelousmlops.substack.com/) 132 | [Ahead of AI by Sebastian Raschka](https://magazine.sebastianraschka.com/) 133 | [Underfitted by Santiago](https://underfitted.svpino.com/) 134 | [Seattle Data Guy Substack](https://seattledataguy.substack.com) 135 | [Deeplearning AI](https://www.deeplearning.ai/the-batch/) 136 | --------------------------------------------------------------------------------