5 Data Science Projects that will Get You into Big Techs | Ex-Google, Microsoft скачать в хорошем качестве

5 Data Science Projects that will Get You into Big Techs | Ex-Google, Microsoft

If you're aiming to work in Data Science, here are five projects that will genuinely prepare you for the job market in 2026. And no- I'm not talking about the Titanic survival model. I'm not talking about the Iris dataset. And I'm definitely not talking about MNIST digit classification. Those projects teach syntax. But they don't teach how data science actually works inside companies today. I've been in this field for over ten years. I've reviewed hundreds of portfolios. I've hired data scientists. And I can tell you- the projects that land jobs in 2026 look nothing like the tutorials you see online. What hiring managers want now are end-to-end, business-aligned projects. Projects that show you understand the problem, the data, the tradeoffs, and the impact. In this video, I walk you through all five projects with specific examples, datasets, and resources you can use to start building right now. The 5 Projects: Customer Segmentation & Retention Analysis Demand Forecasting / Time Series Modeling NLP-Based Insights from Unstructured Data Experimentation & Uplift Modeling End-to-End ML System with Deployment You don't need to do all five. If you build even three of these well- with clean storytelling, sensible metrics, and thoughtful business framing- you're already ahead of most applicants. 💬 Drop a comment: Which project are you going to start with? Chapters: 00:00 – Why Classic Projects Don't Work Anymore 01:00 – Who I Am & Why This Matters 01:25 – What Hiring Managers Actually Want in 2026 02:26 – Project 1: Customer Segmentation & Retention Analysis 04:28 – Project 2: Demand Forecasting / Time Series Modeling 07:03 – Project 3: NLP-Based Insights from Unstructured Data 09:26 – Project 4: Experimentation & Uplift Modeling 11:47 – Project 5: End-to-End ML System with Deployment 13:40 – Quick Recap & Final Advice 13:54 – Free Resources & Outro Free Resources Mentioned: Datasets Kaggle Telecom Churn Dataset: https://www.kaggle.com/datasets/blast... Kaggle Online Retail Dataset: https://www.kaggle.com/datasets/vijay... M5 Forecasting (Walmart Sales): https://www.kaggle.com/competitions/m... UCI Energy Consumption: https://archive.ics.uci.edu/ml/datase... Amazon Product Reviews: https://www.kaggle.com/datasets/snap/... Yelp Open Dataset: https://www.yelp.com/dataset Hugging Face Datasets: https://huggingface.co/datasets Tools & Libraries Prophet (Meta's Forecasting Library): https://facebook.github.io/prophet/ MLflow (Experiment Tracking): https://mlflow.org/ Weights & Biases: https://wandb.ai/ Streamlit (Data Apps): https://streamlit.io/ Gradio (ML Demos): https://gradio.app/ FastAPI (Prediction APIs): https://fastapi.tiangolo.com/ Sentence Transformers: https://www.sbert.net/ Recommended Reading Netflix Tech Blog (Experimentation): https://netflixtechblog.com/ Uber Engineering Blog: https://www.uber.com/blog/engineering/ 🔔 Subscribe for more AI/ML career tips, free resources, deep-dive educational explainers, and my personal journey navigating life in the US as an immigrant while building a career as an AI leader.