15 / 3 / 2026

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level 0 tasks

Task 2: API

in this task I learned that API (apllication programming interface) is a set of rules which allow two applications to interact with each other. It acts as a bridge between two applications where one asks for data and the other gives the required data. API is used cause it is secure and easy for user to collect data from existing servers I also build a simple webpage(by html) that collects requested data(predefined) from the server and displays in on the screen, the data is requested and collected by the api API used:https://pokeapi.co/api/v2/

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Task 3: Github

in this task I learned about github, what it is and what is it usaully used for. Github is a place where people store and manage code and data. It can also be viewed by other people, you can easily propose changes or directly change codes stored in github. in this task, I first forked a repositary (created a copy of the repo) to my github, cloned the repositary and created a new branch to rectify the error with changing the code directly then merged the branch to apply the change after which< i pull requested to the original source code to update the error.

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Task4: Get familiar with the command line on ubuntu and do the following subtasks:

• created a folder named test
• i navigated to the folder in command prompt using cd test
• I created blank file without using text editor type nul > file1.txt and type nul > file2.txt
• using loop i created multiple folders for /L %i in (1,1,2600) do mkdir Folder%i
• i wrote text into it using commnand
  • echo This is file1 > file1.txt
  • echo Hello from file2 > file2.txt
• then i read the output via command type file1.txt file2.txt

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Task 5:

• here first import the csv file using pandas
• then i select only numerical values from the dataset as linear regression works only with numbers
• when i tried to get value of slope from the data set i got a very weird number beacuse the dataset has some blank spaces, which i fill by replacing them by the mean of that column
• then I split the dataset in 2 parts, input value/ x variable/ number given and output value/ value to be predicted
• i split the dataset into training and tesing data
• i normalize the x variable before i use it for ploting or calculations
• using gradient descent i try to find the best fit line which gives me least error
• after i get the best fit line, i get the predicted values of the x variables and compare it to the actual values
• i check the error both code gives and see if the error is in excebtable range(accuracy of model is decent)
• i plot both the graphs and in both of them i print the points and bestfit line

task5.ipynb

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

In this task i learned a bit about numpy
In this task a scrambled matrix was given which i fixed by transposing it and resized the matrix to get a proper image code

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Task 7: Create a Portfolio Webpage

In this task I created a webpage with my portfolio as the content. I used HTML to make the webiste and uploaded the code ontu github repositary Open Website

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TASK 8: Writing Resource Article using Markdown

Report Article

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Task 9: TinkerCAD

tinkerCAD is an online application where you can design 3D models, to show codeblock, and to design circuits online.
In this task I learned about basics of tinkerCAD, and Created a radar system utilising an ultrasonic sensor and servo motor to detect objects within a certain range.

• Arduino uno -> is a simple microcontroller, which reads the inputs and gives output
• ultrasoic sensor ->sends is used to read if any object is in front, it does by sending ultrasonic waves and reading if it gets reflected back, it calculates distance based on how much is taken in between
• servomotor -> a simple motor which rotates up to 180 degrees, it is used here to give the ultra sonic sensor more range

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TASK 10: Speed Control of DC Motor

In this task, i learned to control the speed of a BO Motor using a L298N motor driver and an Arduino board
L298N motor driver is used to change the direction of the motor roating, it works as a H-Bridge(which can change the direction of current flow) and the Arduino board is used for controlling the speed of motor by changing the amount of current send to the motor with the concept of pulse with modulation(you send current with intervals with drops the net volatge of current sent)

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Task 11: LED Toggle Using ESP32

In this task I learned about ESP32 and basic circuit building.
ESP32 is a microcontroller with built in wifi and bluetooth which makes wireless connections possible.
in this task, I build a small circuit and connected it to a ESP32 which is connected to your local wifi and builds a simples webpage which has buttons to turn on and off the LED connected to the ESP32 remotely.

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Task 12: Soldering Prerequisites

Soldering is the process of connecting two electronic components together, so the circuit does not break easily. It is done by melting a metal alloy(tin and lead in the ratio of 65;35) it is mainly used to build or repair damaged circuits and building PCBs.
I learned about the basics of soldering and materials generally used which include

• soldering iron -> the device which melts the solder and is held by the user
• solder wire -> the metal alloy which is melted and which connects two components
• flux -> as the soldering iron heats up it may oxidies or have some impurites which is cleaned with a flux

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Task 14: Karnaugh-map

in this task I learned about karnaugh map

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TASK 15: Active Participation

I participated in a vibe coding hackaton organised by Entrepreneurship Cell

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Task 17: Introduction to VR

Virtual reality (VR) is a simulated experience that employs 3D head-mounted displays and pose tracking to give the user an immersive feel of a virtual world.
Virtual reality is a simulation of something, which looks similar to our surroundings, we feel we really are in a new place or something is really is front of us when nothing in reality changes, more like a reality created "Virtual" reality Virtual reality aims to create a virtual experience with headsets and tracking to place the user in a different world. Augmented reality focuses on augmenting the physical world with digital artifacts, images, videos, or experiences overlayed with computer-generated imagery (CGI) and 3D models.
virtual reality is like you are entering a new environment the living enter the reality of virtual while Augmented reality is like virtual comes to the reality of living. eg in Pokemon go using AR you can place your pokemon on a surface, it seems that the virtual creature entered the living realm while for VR we humons enter the world of fiction like games.

• Nvidia announced back at GDC earlier this month that it was upping framerate on its GeForce NOW cloud gaming service for VR headset streaming

Top VR News — VRDB Augmented Reality vs Virtual Reality — Coursera article{:target="_blank"}

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Task 20 : Notebook Ninja – Getting Started with Jupyter

In this task, i learned to use Jupyter Notebook, which is extremely useful and simple to use, It is also excellent to read and manage code due to it having both pyton and markdown options easily available View My Jupyter Notebook

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Task 21: Watch & Reflect – Intro to Machine Learning

1. statquest explains ML is not just coding but a computer recognising pattern and using it to predict the future, he also about training data and why do we usually use a straight line which ic fit to the model instead of a squiggle, it is so that the accuracy remains high even tho the squiggle fits the data perfectly the point of ML algorithms is to predict values, the squigle gives a much higher error than a staright line fit to the training data. he also states that testing data is used to evaluate the model and just because the model fits the training data, it doesnt mean it will fit the testing data perfectly
2. Data preperation by AltexSoft it explains the main issue of bais in ML algorithm which is faulty dataset. it also explains amount of data is required to model, which is related to the problem, it also states that qualilty of model matters. the video also explains the concept of supervised learning and the type of data used "labelled". it also explains the concept of dimensionality reduction and why is it importnant, which is to remove unwanted columns to help boost the performance of the model, it is a step done while cleaning the data. it also explains why sampling is impoertant, it is to remove bais towards minority sample data. The video also explains about formating and normalization of data. it helps get the scale of data so wrong value is not given more priority, it also explains a basic method of normalizzation which is Min-Max Normallization it also explains the concept of feature engineering, which is opposite to cleaning which is adding more columns to increase the predictive capability of the model

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