💻 Software & Environment Setup
Data Science & Analytics
The computational toolchain and environment used throughout Basics of Supervised and Unsupervised Learning.
Basics supervised unsupervised learning courseBasics supervised unsupervised learning online trainingBest basics supervised unsupervised learning certificationBasics supervised unsupervised learning for researchersBasics supervised unsupervised learning hands-on workshopLearn basics supervised unsupervised learning
# Recommended conda environmentconda create -n dstc_env python=3.11 -yconda activate dstc_envpip install numpy pandas scikit-learn matplotlib seabornPython 3.11 + Jupyter
Interactive analysis notebooks
Interactive analysis notebooks
pandas / NumPy
Data wrangling & numerics
Data wrangling & numerics
scikit-learn
Modelling & evaluation
Modelling & evaluation
Plotly / Seaborn
Statistical visualisation
Statistical visualisation
Supported OS: Linux (Ubuntu 22.04+), macOS, or Windows via WSL2.
Hardware: 16 GB RAM minimum; a CUDA GPU helps for deep-learning modules.
Earn government-registered certification in Basics of Supervised and Unsupervised Learning
e-Certificate and e-Marksheet issued on successful completion.
