💻 Software & Environment Setup
Data Science & Analytics
The computational toolchain and environment used throughout Advanced Data Science Techniques for Academicians.
Academic training for researchersAdvanced science techniques training United KingdomAdvanced science techniques training course for researchersAdvanced science techniques for PhD researchersEda training for researchersScience training for researchers
# 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 Advanced Data Science Techniques for Academicians
e-Certificate and e-Marksheet issued on successful completion.
