A collection of learning resources curated by the DareData network.
| Name | By | Description | Time | Difficulty | Price |
|---|---|---|---|---|---|
| Starters Academy | LDSA | Learn the fundamentals of data science and specialize on data wrangling, time series forecasting, NLP and model deployment. This course prepares you for a career in data science with hands-on projects. | 8 months | Intermediate | € 500 |
| Data Scientist: Machine Learning Specialist | Codecademy | Gain skills in data analysis, machine learning, neural networks, and more, while working on practical projects for real-world application. | 35 weeks | Beginner | Subscription |
| Machine Learning Zoomcamp | DatatalksClub | Covers machine learning algorithms in Python and model deployment using Flask, TensorFlow, and Kubernetes, with a focus on real-world application. | 4 months | Beginner | Free |
| Deep Learning Specialization | Coursera / DeepLearning.ai | Up to date version of the most famous Deep Learning MOOC, learn how to create your own Neural Networks. | 3 months | Intermediate | Free |
| Name | By | Description | Category | Added by | Comments |
|---|---|---|---|---|---|
| The Power of Habit | Charles Duhigg | In The Power of Habit, business reporter Charles Duhigg takes us to the thrilling edge of scientific discoveries that explain why habits exist and how they can be changed. | Management&Business | Ivo | Great to understand how to build more powerful habits. If you are having trouble setting routines of work, you should give it a try! |
| How Big Things Get Done | Bent Flyvbjerg | Nothing is more inspiring than a big vision that becomes a triumphant, new reality. Think of how the Empire State Building went from a sketch to the jewel of New York’s skyline in twenty-one months, or how Apple’s iPod went from a project with a single employee to a product launch in eleven months. | Management&Business | Ivo | Interesting to understand why big projects work or fail |
| Designing Machine Learning Systems | Chip Huyen | Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. | Machine Learning | Ivo | Great introductory book to MLOps and the need to use MLOps systems |
| Personal MBA | Josh Kaufman | Josh Kaufman founded PersonalMBA.com as an alternative to the business school boondoggle. His blog has introduced hundreds of thousands of readers to the best business books and most powerful business concepts of all time. Now, he shares the essentials of entrepreneurship, marketing, sales, negotiation, operations, productivity, systems design, and much more, in one comprehensive volume. The Personal MBA distills the most valuable business lessons into simple, memorable mental models that can be applied to real-world challenges. | Management | Ivo | Cool book for an introduction on management topics. |
| Lean Startup | Eric Ries | The Lean Startup approach fosters companies that are both more capital efficient and that leverage human creativity more effectively. Inspired by lessons from lean manufacturing, it relies on “validated learning,” rapid scientific experimentation, as well as a number of counter-intuitive practices that shorten product development cycles, measure actual progress without resorting to vanity metrics, and learn what customers really want. | Management | Sofia | An approach to create innovative businesses/products that are really needed |
| Name | By | Description |
|---|---|---|
| DareData Foundations LP | DareData Engineering | Where Data Scientists go to get out of notebooks! |
| DareData PyTorch Fundamentals | DareData Engineering | Repo with course on PyTorch Fundamentals, where you'll learn how to work with tensors and the deep learning library. |
| Article | By | Description |
|---|---|---|
| Manager & Makers Schedule | Paul Graham | Programmers often dislike meetings because they operate on a maker's schedule, which values larger blocks of time for deep work |
| Async work | calm.io | Create an environment where you can always get help and nobody can interrupt you |