base on # Perfect Roadmap To Learn Data Science In 2024 [](https://youtu.be/N7RU6W4hAMI) ## Work Of Data Scientist?   ## 1. Python Programming Language -1 Month #### Python:  1. Complete Python Playlist In English: [](https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVNUL99R4bDlVYsncUNvwUBB) 2. Complete Python Playlist In Hindi: [](https://www.youtube.com/watch?v=MJd9d9Mpxg0&list=PLTDARY42LDV4qqiJd1Z1tShm3mp9-rP4v) 3. Flask Playlist: [](https://www.youtube.com/watch?v=4L_xAWDRs7w&list=PLZoTAELRMXVPBaLN3e-uoVRR9hlRFRfUc) ### Final Goal Outcome: 1. Basic To Intermediate Python With various knowledge of various Data structures like numpy,pandas,matplotlib and many more. 2. Knowledge of performing EDA,Feature Engineering and creating visualization charts using python 3. Atleast Make some python projects using Frameworks such as Flask with deployment Eg: Web Scrapping Projects ### What's New In Python 3.12.0 https://docs.python.org/release/3.12.0/ ## 2. Statistics  1. English: 7 Days Statistics Live Session : [](https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay) 2. Statistics in ML(43 videos): [](https://www.youtube.com/watch?v=zRUliXuwJCQ&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO) 3. Stats Hindi Playlist: [](https://www.youtube.com/watch?v=7y3XckjaVOw&list=PLTDARY42LDV6YHSRo669_uDDGmUEmQnDJ) ### EDA 1. EDA Live :[](https://www.youtube.com/playlist?list=PLZoTAELRMXVPzj1D0i_6ajJ6gyD22b3jh) 2. EDA Detailed Playlist:[](https://www.youtube.com/watch?v=ioN1jcWxbv8&list=PLZoTAELRMXVPQyArDHyQVjQxjj_YmEuO9) ### Feature Engineering 1. Complete Detailed Feature Engineering: [](https://www.youtube.com/watch?v=6WDFfaYtN6s&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN) 2. Live EDA Feature Engineering Playlist: [](https://www.youtube.com/watch?v=bTN-6VPe8c0&list=PLZoTAELRMXVPzj1D0i_6ajJ6gyD22b3jh) ### Final Goal Outcome: 1. Techniques to Perform Statistical Analysis 2. Familiar with all concepts which will be important for Machine Learning ## 3. Databases 1. Mongodb: [](https://www.youtube.com/watch?v=magzEfYqIos&list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I) 2. Mysql: [](https://www.youtube.com/watch?v=us1XyayQ6fU&list=PLZoTAELRMXVNMRWlVf0bDDSxNEn38u9Cl) 3. Apache Cassandra Database: [](https://cassandra.apache.org/_/index.html ) ### 4. Machine Learning 1. Live ML Playlist: [](https://www.youtube.com/watch?v=z8sxaUw_f-M&list=PLZoTAELRMXVPjaAzURB77Kz0YXxj65tYz) 2. Complete ML Playlist: [](https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe) 3. Hindi: ML Playlist: [](https://www.youtube.com/watch?v=7uwa9aPbBRU&list=PLTDARY42LDV7WGmlzZtY-w9pemyPrKNUZ) ### 5. Deep Learning Playlist: 1. 5 Days Live Deep Learning Playlist: [](https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns) 2. Complete Deep Learning Playlist: [](https://www.youtube.com/watch?v=YFNKnUhm_-s&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi) 3. Deep Learning Playlist In Hindi: [](https://www.youtube.com/watch?v=SlbbvhO3jKY&list=PLTDARY42LDV4Ic6ZPHIh_CdlPwkKDJmpk) ### 6. NLP Playlist: 1. English: Live NLP Playlist: [](https://www.youtube.com/watch?v=w3coRFpyddQ&list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn) 2. Complete NLP Playlist: [](https://www.youtube.com/watch?v=fM4qTMfCoak&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm) ## Important Frameworks for Production Deployments - Flask Detailed Playlist In English:[](https://www.youtube.com/watch?v=4L_xAWDRs7w&list=PLZoTAELRMXVPBaLN3e-uoVRR9hlRFRfUc) - Flask One Shot Hindi: [](https://www.youtube.com/watch?v=KF-rDqQfqz0) - Gradio Framework: [](https://www.youtube.com/watch?v=wruyZWre2sM) - BentoML: [](https://www.youtube.com/watch?v=i_FtfdOKa2M) - MLflow and Dagshub: [](https://www.youtube.com/watch?v=qdcHHrsXA48) ### 7. MLOPS (Machine Learning Operation)  **Live MLOPS Playlist** : [](https://github.com/features/actions) [ 1. Github Action CI/CD pipelines [](https://github.com/features/actions) [](https://www.youtube.com/watch?v=p7V4Aa7qEpw&list=PLZoTAELRMXVOjQdyqlCmOtq1nZnSsWvag&index=3) 2. Circle CI [](https://circleci.com/docs/) 3. Kubeflow [](https://www.kubeflow.org/docs/) 4. MLflow [](https://mlflow.org/docs/latest/index.html) []([https://www.youtube.com/watch?v=8vmKtS8W7IQ](https://www.youtube.com/watch?v=pxk1Fr33-L4)) 5. Deployment Technqiues In AWS,AZURE, GCP,Dockers And Kubernetes 6. Evidently AI [](https://www.evidentlyai.com/) [](https://www.youtube.com/watch?v=cgc3dSEAel0) 7. Grafana(Monitoring) [](https://grafana.com/) 8. AirFlow [](https://airflow.apache.org/) 9. BentoML [](https://www.youtube.com/watch?v=i_FtfdOKa2M) 10. AWS Sagemaker [](https://www.youtube.com/watch?v=Le-A72NjaWs&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=16) 11. DVC [](https://dvc.org/)[](https://www.youtube.com/watch?v=mHQPzVse2oA) 12. Dockers [](https://www.youtube.com/watch?v=8vmKtS8W7IQ) #### End To End ML,DL,NLP Projects With MLOPS With Deployment And Open Source Tools 1. End To End ML Projects Playlist In English: [](https://www.youtube.com/watch?v=S_F_c9e2bz4&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=1) 2. End To End ML Playlist In Hindi: [](https://www.youtube.com/watch?v=NuwUnRpxq2c&list=PLTDARY42LDV7jzL_f68SY-eOQ9tY2lYvR) ### Machine Learning, Deep Learning, and NLP Projects 1. **First End-To-End ML Project for Starters [Student Performance Prediction]** [](https://www.youtube.com/watch?v=Rv6UFGNmNZg&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=2) 2. **End-to-End NLP Project with GitHub Action, MLOps, and Deployment [Text Summarization]** [](https://www.youtube.com/watch?v=p7V4Aa7qEpw&list=PLZoTAELRMXVOjQdyqlCmOtq1nZnSsWvag&index=3) 3. **End-to-End ML Project Implementation Using AWS Sagemaker** [](https://www.youtube.com/watch?v=Le-A72NjaWs&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=16) 4. **Computer Vision: End-to-End Cell Segmentation Using Yolo V8** - (Part 1) [](https://www.youtube.com/watch?v=r8l31swbU1g&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=17) - (Part 2) [](https://www.youtube.com/watch?v=eiK-6ZhphiA&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=18) 5. **Deep Learning Project with Deployment, MLOps, and DVC [Chicken Disease Classification]** [](https://www.youtube.com/watch?v=p1bfK8ZJgkE&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&index=14) 6. **End-to-End ML Project with MLFLOW** [](https://www.youtube.com/watch?v=pxk1Fr33-L4) 7. **End-to-End ML Project Implementation with Dockers, GitHub Action** [](https://www.youtube.com/watch?v=MJ1vWb1rGwM) 8. **Langchain Open AI Project** [](https://www.youtube.com/watch?v=_FpT1cwcSLg&list=PLZoTAELRMXVORE4VF7WQ_fAl0L1Gljtar) 9. **Kidney Disease Classification** [](https://www.youtube.com/watch?v=86BKEv0X2xU) 9. **Langchain Open AI Project** [](https://www.youtube.com/watch?v=_FpT1cwcSLg&list=PLZoTAELRMXVORE4VF7WQ_fAl0L1Gljtar) ### 8. Detailed Generative AI And LLM Playlist 1. OPENAI Playlist English: [](https://www.youtube.com/watch?v=CbpsDMwFG2g&list=PLZoTAELRMXVMTWGW9iS45ZTcMsntos6VO) 2. Langchain Playlist: [](https://www.youtube.com/watch?v=_FpT1cwcSLg&list=PLZoTAELRMXVORE4VF7WQ_fAl0L1Gljtar) 3. Google Gemini Playlist: [](https://www.youtube.com/watch?v=CC6qMpqgUMU&list=PLZoTAELRMXVNbDmGZlcgCA3a8mRQp5axb) 4. Live Generative AI Playlist: [](https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLmQAMKHKeLZ-iTT-E2kK9uePrJ1Xua9VL) ### Open Source Contribution [](https://github.com/krishnaik06/The-Grand-Complete-Data-Science-Materials) ## Use Of Chatgpt Or Google Bard Extensively ### Roadmap To Generative AI [](https://github.com/krishnaik06/Roadmap-To-Learn-Generative-AI-In-2024) ## Internships:  iNeuron Internships: https://internship.ineuron.ai/ ## Data Science Tracker Sheet For Learning https://drive.google.com/file/d/18doA_wMja2nAawcE6imIcfnEMf-Pir2n/view ## Youtube Channels For Referring All Videos. Consider Subscribing and pressing the bell icon. - Krish Naik : https://www.youtube.com/@krishnaik06 - Krish Naik Hindi: https://www.youtube.com/@krishnaikhindi - Success Stories By Krish(Coming up): https://www.youtube.com/channel/UCNSHtBgZ3dhcpv190JrK_LQ - Support Channel and Join this channel to get access to perks: https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join our Data Science Project - Instagram [](https://instagram.com/krishnaik06) - Telegram [](https://t.me/+V0UeLG8ji-F8ThNb) ", Assign "at most 3 tags" to the expected json: {"id":"6484","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"