Suggested Practice Projects for Beginners

Overview

This chapter suggests concrete practice projects that you can build with the MATLAB skills from this course. Each project is small enough for a beginner, but open enough that you can extend it as you learn more. The goal is to move from typing isolated commands to planning and finishing complete mini programs.

You do not need to know everything in the course to start these projects. Pick something that seems only slightly above your current comfort level, and let the project guide what you learn next.

General Approach to Projects

When you start any project in MATLAB, it helps to follow a simple workflow. First, write down in plain language what the program should do. Next, split that description into small steps that look like operations you have already seen in MATLAB, such as reading data, computing something, or plotting a figure. Then, turn a few of those steps into short scripts or functions and test them. Finally, combine them into one or more scripts that solve the whole task.

Keep your projects in their own folders, use clear file names, and save intermediate versions as you go. It is normal if the first version is messy or only partly works. You can improve it later once you have something running.

Project 1: Temperature Logger and Plotter

A good first project is to work with simple numeric data and create a basic plot. For example, you can track temperatures over several days and visualize them.

You might start with a plain text or CSV file that contains a column of times and a column of temperatures. Your script can read the file, extract the data into vectors, and create a line plot of temperature versus time. Add labels and a title so the plot is easy to understand.

You can practice computing summary values such as the minimum, maximum, and average temperature. Display these values in the Command Window with formatted text. Try adding a horizontal line at the average value on the plot to see how it compares to the data.

Once the basic version works, you can extend it by importing data from different days into a table and plotting multiple days on the same figure, each with its own color. You can also experiment with saving the figure to a file so that you can share it outside MATLAB.

Project 2: Personal Expense Tracker

A second project idea is to build a simple expense tracker. This project lets you practice tables, basic data analysis, and simple visualization.

You can start by creating a small CSV or Excel file with columns such as date, category, and amount. Your script can read the file into a table, then sort the table by date so you see how your expenses evolve over time.

Next, group the data by category and compute the total amount spent in each category. You can then create a bar plot to visualize these totals. Make sure to label the axes and give the figure a clear title.

As an extension, you can add a script that filters the table to a given date range or category. You can read user input with a simple function, then use logical indexing on the table to keep only rows that match what the user asked for. This project can grow slowly as you learn new table operations and plotting features.

Project 3: Simple Scientific Calculator Script

You can use MATLAB as a calculator, but writing your own calculator script will connect several language basics in one place. Start with a script that defines some input numbers directly in the code and computes quantities like powers, square roots, and trigonometric functions.

Then, extend the script so that it asks the user which operation to perform. You can use simple text menus or read a short keyword from the user. Based on this choice, your code calls the correct part of the script to perform the requested calculation.

You can add functions that compute common tasks such as converting degrees to radians, computing the roots of a quadratic equation, or evaluating simple formulas that you encounter in your studies. As you gain confidence, move some of these tasks into separate function files and keep the main script short and focused on user interaction.

Project 4: Data Cleaning and Summary Report

Many real data sets contain missing values, unusual numbers, or inconsistent formats. A simple data cleaning project can help you practice working with arrays, tables, and logical indexing.

Start with a small data file that intentionally contains some missing entries or outlier values. Your script can read the data and identify missing values with built in tools. Once you locate the missing entries, decide on a simple strategy to handle them, for example removing affected rows or filling them with reasonable estimates.

After cleaning the data, compute a short summary report with basic statistics such as mean, median, and standard deviation for one or more variables. You can display this report in the Command Window, or write it to a text file so you can look at it later.

As a next step, connect the cleaning and summary report to a quick visualization, for example before and after histograms of one variable. This helps you see the effect of your cleaning steps and gives you practice combining analysis and plotting in one script.

Project 5: Basic Image Explorer

A small image project is a fun way to see immediate visual results from your code. Begin with a few image files in one folder. Your script can list the images, let you choose one, then read and display it.

Next, add simple transformations such as converting to grayscale, resizing, or rotating. Display the original and transformed images side by side with subplots or a tiled layout. You can experiment with adjusting brightness or contrast using basic operations on the pixel values.

If you want a little more challenge, add code that saves the transformed image under a new file name. Later, you can wrap some of these transformations into local functions that you call from the main script. This keeps the main flow clear while still letting you experiment with different effects.

Project 6: Signal Plot and Simple Filter

If you are interested in signals, you can create a basic project that generates or loads one dimensional signals and applies simple processing. To start, create a vector that represents a noisy signal, for example a sine wave plus random noise. Plot the signal over time to see its shape.

Add a second vector that represents a smoothed or filtered version of the signal by using simple operations that average neighboring points. Plot the filtered signal together with the original so that you can compare them directly.

Later, you can read a real audio file, extract one channel as a vector, and apply similar basic operations. You can visualize the waveform, compute basic statistics, and listen to the difference before and after your processing. Each of these steps links abstract array operations to a signal that you can hear and see.

Project 7: Text and String Analyzer

Working with text is a good way to practice string operations and simple logic. A small project idea is a script that reads a text file and computes counts such as the number of lines, words, or certain keywords.

You can start by loading the entire file content into MATLAB, then split it into words or lines. Count how many times specific words appear by comparing strings. Display the results in an easy to read format in the Command Window.

To expand this project, create simple functions that search for patterns, such as lines that contain a particular word, and return their positions. You can also experiment with basic cleaning, such as converting all text to lower case before counting, to avoid treating different capitalizations as different words.

Project 8: Simple Game or Interactive Tool

Even very small games or interactive tools can be motivating practice projects. One simple example is a number guessing game. The script picks a random integer in a certain range, then the user repeatedly enters guesses. The script responds with hints such as “too high” or “too low” until the user finds the correct number.

This type of project lets you practice loops, conditional statements, and user input. Once the basic version works, you can add a limit on the number of guesses, or display a simple score based on how fast the user finds the answer.

Another idea is a small unit conversion tool, such as converting between different temperature scales or between different distance units. The user chooses a conversion, enters a value, and the script returns the converted result. This type of interaction is simple to build and shows how MATLAB can support everyday tasks.

Project 9: Mini Time Series Dashboard

If you have any data recorded over time, such as daily steps, study hours, or simple measurements, you can turn it into a small dashboard.

Your script can read the data into a table or array, convert the date information into an appropriate time format, and create plots that show the variable over time. Add summary panels that compute totals or averages over weekly or monthly periods.

You can also include simple interactive features such as selecting which time range to plot by adjusting some variables at the top of the script. This lets you see how small parameter changes affect the visual result without changing the core logic.

How to Choose and Grow Projects

You do not need to complete every project idea. Choose one or two that match your current interests, such as numbers, images, text, or interaction. The most useful projects for learning are those that you are curious about and that connect to real data or problems you care about.

Once you complete a basic version of a project, resist the urge to immediately start a completely different one. Instead, spend some time cleaning up your code, reorganizing scripts into functions where it makes sense, and adding comments that explain the main steps. This deepens your understanding and prepares you to extend the project later.

Over time, you can combine ideas from different projects. For example, you can build a small app that loads data, cleans it, analyzes it, and displays plots or images in one place. When you notice yourself repeating similar tasks, consider turning them into reusable utility functions that you keep in a separate folder.