Posted on: 5th Jan 2026

CM2015 Programming with Data Midterm Coursework Assignment

CM2015 Midterm Coursework Assignment

This coursework is worth 50 marks.

Chatbot Project

Now that you have had a chance to explore some techniques and tools in Python, it is time to start integrating them into your own chatbot project. This is a chance for you to build a practical application using your knowledge of Python and Data Programming.

Expectations

  • Develop a functional and interactive chatbot without errors.
  • Demonstrate a strong use of core Python concepts, including:
    o Data structures (dictionaries, lists, tuples) to managing intents, patterns, and responses. o Using Conditional logic and loops appropriately to drive chatbot interaction.
    o Implementing functional and modular programs breaking logic into clear, reusable functions with well-defined inputs and outputs. o Organising code into multiple files (code + data) or modules to enhance maintainability and readability.
  • Adopt software engineering best practices by keeping code modular and reusable using functions, classes (optional), and configuration files (e.g., JSON).
  • Write test cases to verify and highlight the chatbot’s functionality and robustness.
  • Include clear and consistent documentation using comments.
  • Utilise Data Processing Techniques to clean and tokenise input data (e.g., user queries or pattern sets).
  • Uses libraries like NLTK, re (regex) for pattern matching, and tokenisation.
  • Implements basic NLP features, such as stop word removal, stemming/lemmatisation, or part-of-speech tagging.
  • (Optional) Incorporates sentiment analysis, keyword extraction, or named entity recognition for more intelligent responses.

Submission Requirements

For the midterm coursework, you will submit the following documents on the submission page:

  • A shareable link to the Jupyter notebook environment that has o A single Jupyter notebook file with chatbot demo (ipynb file) o Supplementary dataset (intents.json file). The dataset (intents.json) should not be more than 10MB in total size.
    o A PDF report
  • Project ZIP file o ZIP file with all the files in the Jupyter notebook environment (ipynb, intents.json, PDF).
  • An exported HTML file o Export the Jupyter notebook code into a HTML file and submit it.
  • PDF report o A copy of the PDF report.

CM2015 Programming with Data Midterm Coursework Assignment Guide

CM2015 Marking rubric

The marking rubric includes a description of expectations and deliverables. Sections and corresponding marks given below.

Sub

part

Criteria Marks awarded Mark breakdown
1 Title/Domain of chatbot 1 Provide the title of chatbot in the Jupyter notebook
2 Main loop 3 Chatbot uses a main loop that takes in user input and terminates only when the user types “exit” or “quit”.
3 Data Structures 3 The data structures used to manage intents, patterns, and responses are compact and involve the use of Python dictionaries.
4 Code

organisation

5 The different chatbot components are specified as functions that are called from the main loop or other associated functions. This includes:

  • Function to load intents from JSON files
  • Function to load and search using regex patterns
  • Function to generate responses.

Correct Interaction between main loop and functions (argument passing and return calls).

5 Pattern recognition 5 The chatbot must use pattern recognition incorporating regular expression-based matching.

Students are expected to:

  • Write flexible pattern matching statements to recognise multiple instances of the same intent type.
  • Utilise basic regex constructs (e.g., \d, \w, ., *, +, ?) for robust pattern handling.
  • Build regex patterns that account for variations in user input (e.g., case insensitivity, optional words).
  • (Optionally) Implement advanced regex features like grouping, or lookaheads for more nuanced understanding.
6 Response generation 5 The chatbot must demonstrate diversity in response generation. The basic functionality involves retrieving one response for one input. Implement these additional techniques for more diverse responses:

  • Choose responses randomly from a list of options.
  • Applying dynamic strings substitutions with a memory (e.g., store user’s name or colour or some personal information in an object and substitute it in a response).
  • Combination of techniques mentioned above.
7 File usage 5 To promote modularity, reusability, and scalability, all chatbot data including intents, patterns, and responses must be stored and loaded from external JSON files. Key expectations include:

  • Each intent should contain a list of regexbased patterns stored in the JSON file.
  • Responses should be written as template strings in the JSON file. These templates can include placeholders (e.g., {name}, {color}) that are dynamically filled at runtime using string substitution based on user input or stored memory.
  • The chatbot should implement a function that loads the JSON file at runtime, extracts patterns and responses, and builds internal structures such as pattern2intent and intent2response dictionaries.
8 Preprocessing 5 Expectations regarding text preprocessing techniques include:

  • Splitting user input into individual words or tokens to analyse structure and meaning more easily.
  • Eliminating characters like commas, or periods that are not essential for intent detection.
  • Reducing words to their root form to match patterns more broadly and accurately.
9 Other Advanced features 3 Any other advanced feature that you have added and features that you have added beyond lecture material.
10 Process

reflection

5 Discuss the week-by-week iterative development of your chatbot. What was the feedback you received? How did you work on the feedback to improve chatbot? What new features did you add?
11 Report 5 Report should cover the main aspects of chatbot such as:

  • Chatbot application (e.g., use-case, domain of operation).
  • Describe 3 different test cases that clearly illustrate chatbot behaviour.
  • Any other steps to organise data/code that you implemented.
  • Describe advanced techniques that you used.
12 Code 5 Code should:

  • Be reproducible in the current notebook format including making relevant data sources and libraries accessible and explicit.
  • Use proper conventions e.g. relative path vs absolute.
  • Be explained or described where libraries are used in relation to their utility/ability to solve a particular problem in an efficient manner.
  • Notebooks should be structured with a logical set of processes/procedures including clear, logical headings.
  • Not overly verbose e.g. including comments to describe print statements.

[END OF COURSEWORK ASSIGNMENT]

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