The roadmap to learning Data Science and industry-ready projects in 2024 is a wild ride of free videos and materials. Starting with Python and moving into deep learning and NLP, the journey includes end-to-end projects and ML operations. It’s all about democratizing AI and building a strong foundation, with internships as the key to success in the industry. Let’s dive in and level up together! ππ₯π
π Introduction
The video provides an overview of the roadmap to learning data science in 2024. It focuses on topics such as data science, different tools, generative AI, and various projects that have been created over a span of 5 years.
The roadmap also delves into the details of datasets, database usage, hyper-tuning, deployment, and model retraining.
π οΈ Understanding the Roadmap
The first step in understanding the roadmap is to acquire the necessary skill set, including programming knowledge. Python is extensively used and understanding its libraries is crucial.
Key Takeaways:
- 2024 roadmap focuses on learning data science.
- Knowledge of Python and its libraries is crucial.
- Detailed videos are available in English and Hindi.
β Skill Set Requirement
The roadmap stipulates the requisite skill set needed to learn data science. It emphasizes the importance of programming and provides detailed tutorials on learning Python within a specific time frame.
Key Takeaways:
- Learning Python within a particular time frame is achievable.
- Detailed playlists are available in English and Hindi.
π Data Engineering
Data engineering and the process of feature engineering are discussed in detail. The importance of understanding databases, including MongoDB and MySQL, is highlighted.
Key Takeaways:
- Focus on feature engineering and databases is critical.
- The roadmap emphasizes the importance of understanding MongoDB, MySQL, and NoSQL.
π€ Generative AI Focus
The roadmap discusses the significance of generative AI and its applications. The playlist provides comprehensive knowledge on the subject, including details on modular coding and databases.
Key Takeaways:
- Deep learning playlist provided for understanding RNN, CNN, and NLP.
- Focus on modular coding and databases is essential.
π AI Deployment
The roadmap emphasizes the importance of understanding machine learning operations and their practical application. Tools like CircleCI, Kubeflow, and OpenAI are detailed, with a focus on deployment and machine learning.
Key Takeaways:
- Detailed playlist available for understanding machine learning operations.
- Importance of tools like CircleCI and Kubeflow is highlighted.
π‘ Conclusion
In conclusion, the roadmap to learning data science in 2024 with free videos and materials provides a comprehensive guide to developing industry-ready projects. By focusing on essential skill sets, data engineering, generative AI, and AI deployment, the roadmap aims to democratize AI knowledge.
The journey to becoming proficient in data science and industry-ready projects is well-documented, providing a streamlined path for aspiring data scientists.
Key Takeaways:
- The roadmap aims to provide a streamlined path to becoming a proficient data scientist.
- It emphasizes democratizing AI knowledge through comprehensive and free resources.
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