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VSCode-GitHub-and-Portfolio-Block1

Overview

This first part of Block 1 introduces the tools and working environment that will be used throughout the course.

Learning Objectives

Basic Objectives

The following objectives are fundamental to the course. You are expected to complete the exercises to develop core technical proficiency.

  • Set up VS Code, Git/GitHub, and the Python programming environment
  • Become familiar with procedures for accessing course materials and uploading your work to GitHub

Advanced Objectives

The following objectives contribute to the assessment, which involves creating and maintaining a GitHub profile. This will help you build a portfolio for future coursework and professional use.

  • Create a GitHub profile README.md page using VS Code
  • Create Portfolio 1 for the Block 1 exercises

Learning Resources

You will need to download and install the following software.

Visual Studio Code

Recommended activities:

  1. Explore core functions: https://code.visualstudio.com/docs
  2. Follow Python setup instructions: https://code.visualstudio.com/docs/python/python-quick-start
  3. Explore built-in and AI extensions: https://code.visualstudio.com/docs/intelligentapps/overview

Recommended extensions:

  • Python
  • Jupyter
  • GitHub Copilot
  • Markdown Shortcuts
  • Code Spell Checker

Python

Choose one distribution:

Git

Video Resources (Optional)

Exercises 1

The following exercises should be completed during and after your engagement with the learning resources.

Create a GitHub Profile Page (README.md)

Step 1: Create the Repository on GitHub

Create a public repository that will act as your GitHub profile page.

Steps:

  1. Log in to GitHub
  2. Click New repository
  3. Set:
    • Repository name: your exact GitHub username (e.g. YangWang-Glasgow)
    • Public: enabled
    • Initialize with README: enabled
  4. Click Create repository

Step 2: Clone the Repository

Option A: VS Code (GUI)

  1. Open VS Code
  2. Press Ctrl + Shift + P (or Cmd + Shift + P on macOS)
  3. Select Git: Clone
  4. Paste: 
    https://github.com/your-username/your-username.git
  5. Choose a local folder and click Open

Option B: Terminal

cd your-folder
git clone https://github.com/your-username/your-username.git

Step 3: Edit README.md

  1. Open README.md in VS Code
  2. Write content using Markdown

Template resources:

Markdown references:

Markdown preview in VS Code:

  • Ctrl + Shift + V
  • Ctrl + K then V

Step 4: Commit and Push Changes

  1. Open the Source Control panel
  2. Stage changes (+)
  3. Write a commit message (e.g. update README.md)
  4. Click Commit
  5. Click Push or Sync
  6. Check your GitHub profile page for updates

Submission Instructions

  • Post your GitHub profile link on the Moodle forum
  • The repository must be public
  • Submissions are visible to all students

Exercises 2

Setting Up a Python Environment in VS Code (Using Conda)

This exercise explains how to set up a Python environment in VS Code using Anaconda or Miniconda.

Step 1: Install the Python Extension

  1. Open VS Code
  2. Go to Extensions (Ctrl + Shift + X)
  3. Search for Python (Microsoft)
  4. Click Install

Step 2: Check Conda Installation

Open the VS Code terminal and run:

conda --version

If a version number appears, Conda is installed correctly.

Step 3: Create a Conda Environment

conda create -n course-env python=3.13.1
conda activate course-env

You should see (course-env) in the terminal prompt.

Note that, if you cannot active course-env, try to switch to 'Command Prompt' by

  • press Ctrl + Shift + P
  • Select the terminal profile, type:
Terminal: Select Default Profile
  • From the list, select:
Command Prompt
  • Open a new terminal by Terminal → New Terminal or press Ctrl + `

You should now see a prompt like: C:\Users... (not PS C:...)

  • Activate Conda
conda activate course-env

You should see: (course-env) C:\Users...

Step 4: Select the Interpreter in VS Code

  1. Press Ctrl + Shift + P
  2. Select Python: Select Interpreter
  3. Choose: 
    conda | course-env | Python 3.13.1

Step 5: Install Required Packages

conda install numpy pandas matplotlib

Always activate the environment before installing packages.

Step 6: Test the Environment

Create test.py:

import numpy as np
import pandas as pd

print(np.__version__)
print(pd.__version__)

Run:

python test.py

Step 7: Use Jupyter Notebooks

conda install jupyter

Open a .ipynb file and select course-env as the kernel.
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