S200 - Electives

Be ready for Big Data

Big data is now the buzzword. The advent of the Internet and availability of cheap data storage has caused an explosion of data. Governments and Corporations are constantly looking into transforming data into information, and finally into decisions. Having the skills to develop algorithms to process, analyse and manipulate data is now highly valued.

In this course, students will first be introduced to the fundamentals of database design. Students will learn about relational database models and apply design principles to create databases applicable to real life situations. Students will combine SQLite, a popular database engine module in Python, with other Python modules they have learnt to perform data processing and analytics. This skill has a multitude of applications, across areas such as Finance, Bioinformatics, Supply Chain and Marketing.

Topics:
Analytics & Statistics: Introduction to Statistics | What M&Ms can teach you about Statistics | Descriptive Statistics | Inference Statistics | Application of Statistics | Simple Linear Regression
Pandas: Introduction to Pandas | Pandas DataFrame | Reading JSON, CSV, Excel, HTML and XML Data
Matplotlib and Plotly: Graphing with Matplotlib and Plotly | Visualisation with Matplotlib
SciPy: Introduction to SciPy | Statistical testing with Scipy | Linear Regression
Playing with Real World Data: Data Dot Gov | Kaggle | News Sites and Wikipedia
Final Project: Create your own analytics project to analyse areas you really care about, be it sports, finance or games

Create human-like programs

Ever wondered how Siri was programmed? Want to learn about the self-driving cars which is poised to replace all drivers in the world? In this module, Students learn the fundamentals of Artificial Intelligence and Machine Learning. They will explore the various possibilities involving teaching computers to learn.

In this course, students will get first-hand experience with the fundamental components that make an Artificial Intelligence. Students will be introduced to Machine Learning concepts, including statistical techniques that give computer systems the ability to “learn” with data. Students will work extensively with Pandas, a popular module in Python used for data analysis and machine learning, to analyse real world data and train their own basic learning system.

Topics
Introduction to ML & AI: What is Artificial Intelligence? | What is Machine Learning? | ML Project Development Framework
Data Management: Kaggle | Collecting Data | Managing Datasets | Splitting Data for Training, Validation and Testing | Data Preprocessing
Hypothesis & Modelling: Hypothesis step | Model Creation and Training | Model Fitting | CNN (Convolutional Neural Network)
Evaluation and Interpretation: Model Validation | Loss function | RMSE
Optimisation: Parameter tuning | Overfitting vs Underfitting
Hackathon

Take Your First Step Into The World Of Automation

An Algorithm is essentially the brains behind a computer program. It is a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. Algorithms perform calculations, data processing, and/or automated reasoning tasks. In essence, students’ to understand and develop algorithms to solve problems is critical and would be highly valued in the future world of automation.

In this course, students develop an in-depth understanding of algorithms. They learn to analyse algorithms and develop an appreciation of an efficient algorithm. They will also learn the key algorithms commonly used in programming.

Topics
Introduction to Algorithms: What is an Algorithm? | What is makes an Algorithm good? Analysing an Algorithm with bigO
Sorting and Searching Algorithms: Bubblesort | Shellsort | Mergesort | Quicksort | Binary Search
Application of Sorting and Searching Algorithm Real life application of the basic algorithms learned | Internet search results | How Uber and Grab match you with the right driver
Divide-and-Conquer Algorithm: Basic Recursion | The Maximum Contiguous Subsequence Sum Problem | Analysis of a Basic Divide-and-Conquer Recurrence
Dynamic Programming: Writing Dynamic Programming | Applying Dynamic Programming

Turn your gaming passion into a career

Have a passion for games? Ever wondered about what goes on behind a good game? Our introductory course will bring students through the various components of Game Development using Python Arcade.

Python Arcade is an ideal tool for students learning game development. Its user-friendly interface and powerful features simplify the process of creating 2D games, allowing students to focus on creativity and problem-solving. With clear documentation and beginner-friendly syntax, Python Arcade fosters experimentation and ignites a passion for game development. Mastering Python Arcade equips students with valuable programming skills while paving the way for future success in the industry.

Students in this course will be exposed to critical concepts of Game Design, from analysing games with the elemental tetrad (Mechanics, Aesthetics, Story, and Technology) to creating basic games with their existing knowledge of Python and the exceptional Python Arcade library.

Topics
Introduction: Python Arcade | PyCharm Editor | Platformer Game
Game Development Concepts: What are common components in successful games? | How are the design concepts applied?
Game Design Principles: 2D game engine | Making the game come to life with animations and movements | Adding interactivity among game characters and sound effects
Hackathon

Combining Design with Technology

Do you frequently shop online? Ever wondered about what goes on behind the creation of sites such as Shopee, Lazada or Sephora? This course will bring students through the various components of Web Development. From appreciating the beauty of using the right fonts and colours to designing the page structure, students will learn client side web programming and apply their newfound HTML/CSS/Javascript knowledge to develop websites or web apps that are fluid, interactive and responsive.

Topics
Introduction to Web Development: HTML | CSS | Colours, formats and backgrounds | Page Layout and structure | Positioning basics and floating | Multicolumns
Adding Javascript to your website: Javascript Structure | Embedding Javascript in forms
UI/UX: Enabling Fluid and Responsive Design | Adapting the web page for mobile | Site Map | wireframing | UI/UX

Combining Design with Technology

Netflix, Reddit, Samsung, and Airbnb. These are just some of the many companies in the world using Flask. As a lightweight web application framework written in Python, Flask makes picking up Web App Development swift and simple. This allows users to craft basic web applications as they are just getting started, then having the ability to scale their creations to greater heights to include databases, authentication, and many more features!

Topics
Quick Introduction to HTML: HTML Basics | Bootstrap
Flask: Creating a basic Flask program | Flask Templates | HTML files with static data | Jinja Templating Engine | Web Forms | HTTP requests
Models and Databases: Object Relational Mapping | One-to-Many Relationship
Authentication: Flask-Login Module | User Accounts

Learn to predict the future

Mankind has always been obsessed with predicting the future. No one can claim to have the ability to accurately predict the future, but with the advent of Mathematics and computers, we have equipped ourselves with a tool that makes us more accurate than before. Computer simulation models are used in a huge range of fields such as Financial Trading, Weather Forecasting, War Simulation, Supply Chain Management and Road Infrastructure design.

In this course, students’ knowledge on Math and Probability will be expanded. They will be introduced to famous mathematical and computer simulation models, such as the Monte Carlo method. Students will learn how to use Python modules designed for scientific computing, such as NumPy and Matplot, to build mathematical and computer simulation models of real world systems.

Topics
Introduction: What is modelling and simulations | Examples of M&S - Weather, Flight, Bomb
Probability: Concept of chance | Monte Carlo Simulations | Real world applications in actuarial Science, equities market and nuclear physics
Python Tools: Pseudo random generators | SimPy
Simulating Blackjack: Modelling framework | Understanding the mathematics | Strategies to beat the dealer | Simulating the strategies
Application to Bubble Tea: Modelling customer arrival | Modelling business process | Queuing Theory
Hackathon