Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.
Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
Explains magnetic induction, force on a dipole, torque, and applications in macroscopic systems.
Introduces applied machine learning concepts such as data collection, feature engineering, model selection, and performance evaluation metrics.
Presents a project description for building educational chatbots using ChatGPT-like models, outlining stages, policies, and data sharing for research purposes.
