Skip to content

Latest commit

 

History

History
241 lines (156 loc) · 11.3 KB

File metadata and controls

241 lines (156 loc) · 11.3 KB

Generic Tasks

TASK 1: 3D Printing

Understand the working of a 3D printer, check out the online resources. Understand what's an STL file, and then learn to slice it (using ultimaker or creality slicer).Go through the SOP'S regarding the 3d printer. Learn about bed temperature, infill density and other printer settings. Finally get an STL file from the internet, and slice it and put it for print.

Resources:

Introduction to 3d printer

PLA settings

Types of 3D printing

(Note this task is to be done under coordinator supervision.) 3dprinter

TASK 2: API

What is an API? Learn the working of an API and its applications. Using any api of your choice, build an user interface(web app, mobile app, etc), where you can make calls and then display the necessary information. An example weather app is given below, using the open weather api.

Example

TASK 3: Working with Github

Familiarize yourself with GitHub integrated workflows (GitHub actions), Issues, and pull requests with this task. Given below is a git repository, go check it out and then perform the necessary tasks stated in the readme file.

Check this link for more info: https://github.com/UVCE-Marvel/git-task

TASK 4: Get familiar with the command line on ubuntu and do the following subtasks:

● Create a folder named test.

● cd into that folder.

● Create a blank file without using any text editor.

● list the files in that folder

● create 2600 folders in this folder where each folder is named like . For example, M90 or B56.

● concatenate two text files containing any random text and display them on the terminal.

https://ubuntu.com/tutorials/command-line-for-beginners#1-overview

Task 5 : Build Your Own Brain -Linear Regression from Scratch

Dive into the core of machine learning by implementing Linear Regression from scratch using , and compare its performance with the scikit-learn implementation. Use the California Housing dataset to evaluate your model on real-world data.

Your Task:

  • Implement linear regression manually (without using ML libraries for training).
  • Understand and apply gradient descent to minimize error.
  • Compare your custom model’s performance against sklearn.linear_model.LinearRegression .
  • You should analyze results by:
    • Graph showing line of best fit and the datapoints.
    • Performance metrics: MSE, MAE, R² for both custom and scikit-learn models.
    • Brief comparison between two models.

[Download Dataset](https://www.kaggle.com/datasets/camnugent/california-housing-prices)

Learn Linear Regression:

  1. Understanding :

  2. Coding the linear regression algorithm from scratch:

Expected Outcomes:

  • Grasp how gradient descent optimizes weights in linear regression.
  • Understand the importance of feature scaling.
  • Know how to evaluate regression models using standard metrics.
  • Be able to appreciate the convenience and performance of inbuilt ML libraries.

Precautions:

  • Always normalize or standardize features before training your scratch model, especially if you’re using gradient descent.
  • Be cautious with your learning rate , too small and the model is slow, too large and it may diverge.
  • Initialize weights and bias properly ( small random values or zeros).

Task 6 : The Matrix Puzzle — Decode with NumPy & Reveal the Image

Get hands-on with NumPy and Matplotlib by solving a visual puzzle. You’ll be given a scrambled matrix, and your mission is to decode it into a hidden image using NumPy operations and visualization techniques.

Your Task:

  • Download the scrambled matrix from the link provided.
  • Use your knowledge of NumPy to manipulate, reshape, and reorient the matrix.
  • Reveal the secret image by plotting it using matplotlib.pyplot.imshow() .
  • Scrambled Matrix: Download Here
  • NumPy Learning Doc: Explore Here

Learn NUMPY:

Learn Matplotlib:

Decode the Matrix using these clues and Visualize it :

  • "Try reshaping the encoded array into a square—how many elements are there?"
  • "The structure may be upright, but the data might be sideways. Look at its orientation."
  • "Sometimes the end is actually the beginning."

Expected Outcomes:

  • Gain confidence with NumPy operations like reshaping, slicing, flipping, and transposing.
  • Learn to visualize 2D arrays using Matplotlib.
  • Sharpen your debugging and puzzle-solving skills in a fun context.

Precautions:

  • Check the shape of the array before applying imshow() - wrong dimensions will throw errors.
  • Ensure that your reshaped matrix has the correct number of elements (it's likely a square!).

TASK 7: Create a Portfolio Webpage

Create a website to showcase your portfolio - about yourself, interests, projects, social media profiles and more. It has to be responsive and also pushed to the git repository. CSS can be of your choice and any framework can be used.

TASK 8: Writing Resource Article using Markdown

Markdown is an easy-to-use markup language that is used with plain text to add formatting elements (headings, bulleted lists, URLs) to plain text without the use of a formal text editor or the use of HTML tags. Markdown is device agnostic and displays the writing format consistently across device type. Write a technical resource article on a topic of your choice and post it on the MARVEL website. Refer to the linked article for further details

Link

TASK 9: Tinkercad

Create a tinkercad account, get familiar with the application, understand the example circuits given and simulate a simple circuit using an ultrasonic sensor to estimate the distance between an obstacle and the sensor. Display the results on the serial monitor.

Create a radar system utilising an ultrasonic sensor and servo motor to detect objects within a certain range. The ultrasonic sensor emits sound waves and measures the time taken for them to bounce back, while the servo motor rotates the sensor to cover a wider area, providing a simple yet effective detection mechanism. RESOURCE: https://youtu.be/NwmcNCvUcDc?si=x2LAYMFiqs1SzLfI TASK OUTCOME: introduction to- · TINKERCAD · Working of ultrasonic sensor and servo motor · Radar technology PRECAUTIONS/SAFETY MEASURES- NOT ANY

TASK 10: Speed Control of DC Motor

Explore basic techniques for controlling DC motors, understand the control DC motors using the L298N motor driver and the Arduino board. Using an UNO and H-Bridge L298N motor driver, control the speed of a 5V BO motor, try simulating this on tinkercad and then perform it on the hardware, Record videos of you doing the same.

Reference

TASK 11: LED Toggle Using ESP32

Learn the working of an ESP32 and create a standalone web server with an ESP32 that controls the LED connected with ESP32 GPIOs. Use the arduino IDE to code and upload the program to the ESP32. Learn to configure the IDE to upload code to an ESP32.

Reference

TASK 12: Soldering Prerequisites

(Soldering is to be done in presence of a coordinator)

Learn about the soldering equipment present in our lab, the solder, the soldering iron, soldering wick, flux, etc. Learn to use them and perform basic soldering on a perf board, for example a LED circuit in the presence of a coordinator and document the same.

Reference

TASK 13:

Design a 555 astable multivibrator with duty cycle 60%, rig up the circuit on a breadboard and by using the probes observe the output of your circuit on the DSO. Resources:

Circuit

TASK 14: Karnaugh Maps and Deriving the logic circuit

Description: For 4 cases, based on door lock/open and key pressed/not pressed. Determine the karnaugh map and make a burglar alarm using simple logic circuits. The buzzer or led blinks when certain conditions are met, you can use push buttons for the door and key.

(Tip: use logic gates, use k-maps to figure out the working conditions.)

TASK 15: Active Participation:

Take part in any technical event, inter or intra college and submit the issued certificate of participation.

Enroll for a MOOC and complete the course.

TASK 16: Datasheets report writing:

Topics: 1)MQ135 Gas sensor 2)L293D motor driver Task Description: Study the datasheet of any one of the above and write a report on it. Specify about the ICs used in L293D, PWM, H-bridge etc. In case of MQ 135, specify the calibrations for different gases and the Freundlich Absorption Theorem Graph.

Task 17: Introduction to VR

Familiarise yourself with what Virtual Reality is. Make a detailed study about what's the difference between VR and AR. Mention about the trends in the space and technology stack being developed. Make about Indian companies in this space. Make the report with detail. Using generative AI to generate this study can lead to disqualification.

vrlol

TASK 18: Sad servers - "Like LeetCode for Linux"

Sadservers is an excellent ground to test your Linux troubleshooting skills. Here is a troubleshooting scenario: Command Line Murders. Troubleshoot and Make Sad Servers Happy!

Command line murder
Linux commands
Linux commands

Task 19: Make a Web app

Using express create a resource library website where you can browse the resource articles, books etc which are available and also manage your account
Reference