Forem: Lina Dias

Why is my personal website in pure HTML?

Lina Dias — Thu, 11 May 2023 01:04:32 +0000

Hi there!

I've just updated my personal website (which I don't use as a blog anymore, since I'll post mostly here). Hosted it on Github Pages and everything. Here are 5 reasons I decided to opt for pure HTML in its design, and not any framework:

Honestly, I find it kinda cute (and will experiment on it later)
I was convinced.
I really liked the idea of "Web Design in 4 Minutes" by Jeremy Thomas. And also how my site sounded on Edge's screen reader (which I use to increase attention span).
Looks classic. Takes me back to old-timey Internet! (said the 2001 girl)
It also makes me feel like an actual CS professor, even if there are still a year and a half left before I graduate with my BSc.

That's it, bye!

I'm Back! + On Learning Software Engineering and Managing Failure

Lina Dias — Sat, 29 Apr 2023 03:30:54 +0000

Hi again!
It has been almost 3 years since my last post here, my profile has been accumulating dust, and it's time to shake it off.

I used to write mostly about my learning experiences and how I managed to be productive during the early days of the pandemic, which were also the early days of my Computer Science bachelors' journey. Now that I'm approaching the end of my first 5 years studying CS, new opportunities have appeared, and I'm excited to show you every one of them in small articles like this one.

From late 2021 to 2022, I have gone into (kind of) a slump. I (thought I) couldn't write articles or learn code like I did on my first days anymore, and it demotivated me to horrendous levels. I tried everything: sleeping more, trying to be more active in the gym, establishing a routine, but none of it actually worked until I found my current therapist. If you're procrastinating going to therapy in 2023 just because everyone seems to be doing it, stop right now and schedule your session!

In 2023, I decided to turn my situation upside down and to start looking for jobs in the areas I've identified with the most. After leaving my first scientific initiation due to said crisis, I've found myself since September '22 researching on Computer Vision, but since it's a voluntary position, it's not really doing anything for me, but I found interest in the area and started going after related Master's programs and internships.

Now, to the actual subject of this post!

I had two Software Engineering subjects at uni for the last year, and I have to admit: it was a very difficult time for me. I liked planning and all the tools to do it, but when faced with real-world projects such as Plague.me, in which I helped by being the "front-end and design lead", I saw all the possible failing scenarios you could imagine. In the end, though, I was able to obtain a 9+ for presentation.

Here are some things I practiced for this project:

Number One: The Documentation Nightmare

I thought I liked to write docs in Markdown, up until this point. One of the first tasks we had to do for Software Engineering II (I'm going to skip SWE I because it was mostly planning work I didn't even get to actually use) was to write a tutorial (and record a video version) related to the project in any way. I thought it was a good idea to write about HTTP and how to do server communication with it, since the project was going to be a website.

I think the final product is pretty nice visually, but in the end it hasn't helped me as much as I thought it would.

Number Two: Scrum-Leading my Way to Hell (probably)

I also thought it would be very nice to be the first Scrum leader in the project. We had a total of three professor-supervised iterations, and I knew nothing about Scrum besides what was given in class. I liked the approach, though, and might learn more about agile development in the future.

As a leader, my responsibilities were to report my group's progress to the professor and in the wiki. I might have done a goodish job at managing the group and planning the iteration, but I forgot to complete some data and that cost me some points.

One of my biggest difficulties in this part was to understand the point system that was being used in the planned story of the sprint, but on later iterations I was able to kind of pick that up. I didn't struggle that much managing both being the project leader for two weeks and my front-end/design role, but it got harder when exam season started for all 6 subjects I picked for the semester.

Number Three: (Actually) Doing some Front-end Work! Yay!

As a kid, I loved to have customized Tumblr and Blogger accounts. I'd really be waked up until midnight tinkering with the HTML/CSS file of both and sleep soundly after with no regrets. That's almost how I felt on the first days of trying to create a cute interface for the gamer social media website. Then the self-doubt and the project deadlines came and destroyed it once again.

I would love to play with web design, but not on that level of pressure! In a good note, I learned to deal better with deadlines. Not that I was a big procrastinator, but my mind couldn't revolve around the idea of some things having to be done in less than two weeks.

On this project, I mostly used HTML and CSS with low to no JS code. As an absolute child in Ruby on Rails, I'd edit the layout on Codepen and ask my colleagues (mostly my boyfriend) to help me "translate" it into embedded Ruby, which seemed to work partially for the time frame in question.

Dealing with Self-Doubt and Imposter Syndrome

A lot of resources available on the Internet helped me get through this subject with little damage, and most of it was free:

Free Ruby on Rails courses at Udemy
HTML and CSS cheat sheets!
Youtube tutorials

But nothing seemed to help me with the horrifying vision that, no matter how hard I tried, I wouldn't get anything better than simple and newbie results. I comforted myself at the time thinking that as an actual newbie on programming, that was the most I could do and, eventually, I would overcome this feeling.

In the End, Maybe it Mattered a Little

As I said, it became. During my vacation month (this April), I was able to start building side web projects more confidently and more consistently (I haven't finished none yet as I write this, but I'm really committed!) and I'm thinking of starting some freelance work to help me study for my dream career and graduation plans.

I think the most valuable lesson I was able to get was that real progress is slow, but very rewarding if you do it the right way.

Later I was also able to find resources such as the article "Why Learning to Code is So Damn Hard", by Erik Trautman, which explained a little bit more about how/why could I be in such a slump while learning. I identified myself a lot with the "Desert of Despair" step, but I'm happy it is very close to the "Upswing of Awesome". I hope I can show you my transition into it in the next posts.

Conclusion

I decided to dedicate a lot of time on this post talking about the effects of mental health on my productivity because it really became a part of me during these last years and I hope it wasn't much of a hassle to keep reading. I also want to advocate for the end of hustle culture in programming and studying communities by starting to normalize these struggles on my posts.

If you liked this post format and want me to delve more into it or give me some suggestions, feel free to use the comment section and give me a like! <3

See you soon!

Contemplating Internet Inequality in Brazil

Lina Dias — Tue, 26 May 2020 16:29:10 +0000

Hi everyone! Hope you're doing well during these quarantine days~

While I'm using my mother's computer, waiting for my new PC to arrive, I was approved in a Brazilian program about Internet Governance. I never had the curiosity to learn about it such as in-depth as I am having now. It's a very important topic for us, Internet users, and I hope that you read at least some topics about it after reading this blog post.

As our first task, it was created a mailing list between teams of approved people all over the country and we've been discussing some essential themes and something has been quoted a lot in my team: Internet Inequality.

As young people and mostly not working for the government, we are limited to saying they should invest more in education, accessibility, but as we all know, this is not a big priority for them, since even the President and Education Minister are more worried about defeating the leftists than about doing their work.

Nowadays, with the pandemic, this problem has been highlighted with campaigns such as #AdiaENEM (demanding to cancel/postpone the university entrance exams this year) and local campaigns on public schools and universities for not digitalizing their classes (as a private school would do, for example) before all of the students have access to an Internet connection at their homes.

Remote work has also been seen as a solution to some areas such as journalism, programming, et cetera. But, as this LinkedIn blog post by Camila Achutti (in Portuguese) could tell, not everyone has the perfect conditions to work on-line and this should be considered.

The Internet contains information and resources for better education. While its access is not an actual Human Right, it is the main form of information exchange worldwide and the lack of internet access is a lack of reliable and on-time information. For the UN, as stated in this last hyperlink, it's a way to interrupt access to education and freedom of thought/expression, which are actual Human Rights.

So, how do we democratize this access in the middle of a pandemic that is almost obligating us to find new ways to work, to live our lives differently?

Mostly, when we ask ourselves or even official organs this question, we are spammed by the "with public policies" answer. But which public policies? What are the people we voted doing, for making it a thing? As I write this article, the national research "TIC Domicílios" concluded that 3/4 of Brazilians have access to the Internet at their homes. Brazil is populated by more than 212 million people. That means at least 53 million do not have this access to information. That's a lot.

What are the "public policies" doing to help these 53m people get access to the Internet? I googled it up and almost everything I found is almost outdated - most articles are from the first semester of 2016, when Dilma Rousseff was still our President, four years and two governments ago. More recent governments have been doing few - or even nothing - to promote on-line equality.

That was when the "Marco Civil da Internet" (our net neutrality laws) was approved and started working. Since then, I couldn't search for any relevant public policies on democratizing Internet access. That could mean it's not a priority for the federal government.

Both broadband and mobile connections have a broad reach in the country, excluding only a few areas. But not everyone in the reached areas has access to a smartphone or a computer, for example. I'm not saying the government should simply give all of them an iPhone, but at least they should be aware of this condition when digitalizing documents, creating an app for receiving the emergency help from a bank and other exclusive actions for people who have smartphones.

Let's not forget that this last app has suffered a lot since its beginning, remembering the CPF (our social security number) value in the sign-up page was programmed to be an "integer", not a "char" value, excluding numbers that started with zero and that a LOT of people are robbing identities to receive the money.

So, I guess the population itself has to stand up and fight for its rights to information and connection. But how?

As the #AdiaENEM was made mostly by privileged (but heureusement woke) students who had access to Twitter at the time, we will need people who also have access to help with that fight. But only trending a hashtag may not work as well as it did with the ENEM test. We should create actions and campaigns that actually help to bring the Internet to the less privileged, instead of only contemplating numbers and wondering when will someone do something.

Beyond the access of poor people, we should also consider the access of people with disabilities, people of color, and other minorities, such as women and the LGBTQIA+. That makes it even harder and bureaucratic to plan, even in the long term.

How would you help to solve this problem? Please, leave a comment!

How to online study!

Lina Dias — Thu, 26 Mar 2020 21:36:42 +0000

Hi, everyone!

These days I've been quite busy because I'm studying in my university's original time. This quarantine, as I said before in other posts, I'm focusing on study. Not for going crazy, but for not getting lost when the classes are back. With all this confusion, I'm here to give you some tips about online learning (as I'm almost a pro). These ones have been working very well for me:

1. Create your own study corner

I guess you're thinking about those ones we see on Pinterest and Instagram. But it doesn't need to be "instagrammable" or exactly like that one you liked in 2015: it should be, most importantly, clean and slightly away (according to what you have) from where you rest.

Some tips for study desk organization:
- Clean it before you start;
- Tidy it up, else the mess will annoy you;
- Be original! Each one of us learns in a different way, and so different will be our study corners because of that;
- Your desk doesn't need to be "aesthetically pleasing" in a postable way, especially if you're not recording a study vlog or taking a pic for your Instagram: the most productive it seems for you, the better - before doing more elaborate summaries, I practice writing and the content in a common A4 paper, with common blue, black and red pens you can find everywhere. But, if you feel more inspired by this, and actually CAN do it, go on;
- Isolate yourself from noise by closing your room's door or putting on earphones.

But creating a new space is way beyond decoration! You can create or search Youtube/Spotify playlists if you can study listening to music, but don't let this distract you from your main goal! Avoid "noisy" songs (such as EDM and conventional pop), and choose lo-fi and instrumental music (I recommend this YouTube playlist with all City Girl's full albums).

2. Entertain yourself positively

When you're in your free time, spare some time to watch positive study Youtubers. agra chan (Brazilian Youtuber) has done recently a "study with me" with background music, and it should be used like: you study while the video is playing, letting your device in a corner, listening to the music, as you study "together".

You can also see oh no Nina's "not really studying with Nina" vlogs and some of Jem's videos. Search for "study vlogs" more frequently and you can feel a little more inspired when you're studying.

3. Use productivity apps

For example, you can utilize the Forest app as a time manager for studies. As I study for about 6h/day, it's important to have a 2h alarm (120min) so I can get along with every subject I study. It also blocks the rest of your phone (if you configure it correctly), so you can also use it to avoid distractions. I like to end my months seeing how many trees I've already "planted" in the app.

4. Search for interesting, useful courses

Take the menu of your course, see your subjects, see the course plan of the subjects and try to do something with this information. Knowing I'm getting ahead of the subjects in my course motivates me a lot. If you're in middle or high school, search for platforms that are offering free trials for social isolation, or Youtube channels with videos about the subjects you have more difficulty. Revise the subjects and maybe get ahead of your course too: see your book and the topics of your exams, if you have access to them.

Now, if you're not studying formally, or don't know what to study, search for something to occupy your mind: language courses can be a great idea. Since I've started learning French, I have used Duolingo, which is almost totally for free, and I think it's a great tool for beginners like me. But please don't make your Duo sad.

5. Define your schedule (and please stick to it)

As you're absolutely NOT in a presential course and there aren't any school bells which go like "HELLO, time to your Programming Logic class so WAKE THE F UP", for example, it's important that you can be able to define your study schedule and actually try to stick to it. That makes you associate that specific time of the day to study time and feel more productive.

I am trying to stick to my university's schedule at home and it makes me wake up by 6 AM, take a bath, do my skincare routine, make and eat my breakfast, brush my teeth, maybe listen to some music, and, when it's exactly 8 AM, fly like a cat which saw a cucumber, for my study corner and start calculating integrals or studying data structures, and just "wake up" from the workflow at 10, so I can change the subject, and at 12, so I can eat my lunch. At 2 PM I'm back for the last subject, and at 4 I'm done with everything.

I avoid entering my study room while I'm at the lunchtime (and consequently not 100% done with my study), so I can't damage my study "mental ambient".

(When I wrote this in Portuguese, it was almost 2 PM, so I was in a hurry to finish and post it before I started studying Digital Circuits, but now I've already finished it so bye, I guess?)

Code like a Fullstack girl updates #3

Lina Dias — Sun, 22 Mar 2020 22:43:27 +0000

Hi, everyone!

As I'm tired of saying (and you of reading), I decided to focus almost all of my quarantine time on studying. This first week I've made the Bootcamp "Code like a Fullstack Girl", but I still can't understand how the platform promotes the course as something that "prepares you for the job market" - and even asked my resume for sending the certificate - and at the same time is something almost meaningless.

The platform itself is not that good, and I have zero professional experience inside or not the area and lying just to obtain an ornament for my LinkedIn doesn't look like something someone who's searching for a job and stability would actually do.

I had finished all 21 courses yesterday, as I said I would, and my opinion remains the same: we need more practice and less "pretending to care about your career" stuff. Besides that, why does the course name highlights the presence of women when men have more prominent roles (ranking, teaching...)? How am I supposed to "code like a Fullstack girl" if I'm being taught by men? Actually, is there any difference? Did you think about the diversity of women that could teach and mentor this project?

Even though I disliked many things about these courses, it was good to take notes about platforms, languages, and frameworks which are essential for this career. I can still remember some things that were taught, but I need to exercise my knowledge a lot if I wish to be a full stack developer.

I think that's it for this post so good night!

Code like a Fullstack girl updates #2

Lina Dias — Sat, 21 Mar 2020 23:58:45 +0000

Hi, everyone!

It's good to write in a daily basis and I really want to adapt my routine so I can do this more frequently. I'm trying to be more healthy, eating better, doing some daily exercising (I used to do it only thrice a week), trying to drink 2 litres of water a day (at the moment I wrote this on the Portuguese blog, I had drunk 1l, but as I translate this post, I've already reached 2!) and this kind of things I only think about when I'm - theoretically - bored. I had reached my limit when I tried to drink lemon and cucumber water in the morning. I am not a fan of it neither want to try it again.

These days, as I've already told you, have been wonderful for my studies and my main hobby: to read and to watch things. I also told in the last post I've finished Anne With An E, and I started Itaewon Class today. I still haven't watched it all (until now), but I think the storyline is really interesting and I'm hoping I will be able to get along with it.

This (should be) the second post about the Code Like a Fullstack Girl Bootcamp, from Digital Innovation One. As I had mentioned before, I did 14 exercises in the total but still think about it the same way: I should be able to search more if I'm looking for a complete formation. Classes are good and explanatory, but are way too theoretical and the challenges are just video callings with broken audio.

I hope to complete it today, but I'll only post my final impressions tomorrow. It's not as heavy as I thought it would be, but I am not sad about it. I couldn't expect that much of an online course. They gave me essential topics and I should study, exercise and learn them more deeply if I really want to do it.

With quarantine, I had enjoyed each one of the 24 hours of a day studying or doing something else (like sleeping? That is important, don't forget), and making this Bootcamp available was a great idea. I think about paying more attention to this platform these days to see if they make something else (but related) available, since most courses of them are closed, and the open ones are not of my interest.

Beyond studying, I have been thinking about my academic and professional future. I had signed up for many other classes, including UFRGS-Lumina's Deconstructing Racism Practically. I like the didatics of their courses. There is one, for example, about Greek poetry, in which the professor sings Sappho's (and many others') poetry, and talks about the poets' lives. At the ending, it has a small quiz and that's it.

What have you done these days?

Code like a Fullstack girl updates #1

Lina Dias — Sat, 21 Mar 2020 23:39:52 +0000

Hi, everyone!

I came back with a new post just to talk to you about my new hobby in quarantine: learning!

By the moment I posted this on my Portuguese blog, I had 7 certificates, and I wanted 10. At first, I thought I was going to do 7 a day and end it in 3 days, but as I saw that it looked humanly impossible, I decided to do it the way I could. Actually, this is my third - and the most productive - day doing the Bootcamp. I've learned about Logic, Systems Architecture, Github, HTML/CSS, a little bit of Bootstrap, and other issues.

I believe ending this Bootcamp won't be enough for me, but I'm learning a lot. I need to practice what I'm learning, and not just staying in theory, as I loved to do in my disastrous first semester at uni. I need to read and write code and test it to see if it really works, and if it doesn't, to pass hours trying to discover the reason, as I did in the data science course at Udemy.

I had learned a lot of theory, but I frequently ask myself Where Am I Going To Use This And When. I need more material to know about it, but it was a great start, as I still don't know exactly what my interests in Computing are, and that opened my eyes to many possibilities.

But! I still need to do the other 2/3 of the course, as I just made 1/3 of it to this moment. I hope there are even more things between what I learned until now and the technical knowledge of a full stack developer. And I want to know what are these things as soon as possible.

During quarantine, I decided to learn more. I want to graduate in four years - if the universe allows me to do it - and the faster and more efficient way I can learn what I need, the better this situation will be for me, and sooner I will be able to invest in my own entertainment. In this first week, I've watched the 3 seasons of Anne With an E, and Netflix: how do you dare to sleep at night promoting such things as Elite and 13 Reasons Why and ignoring the masterpiece that is Anne?

Many platforms are open for us to pass this Corona Time with education, and I recommend you to search it up too so you can avoid boredom and not being a full-time desperate mess about isolation.

See you soon!

Going into a Data Science Python course!

Lina Dias — Thu, 19 Mar 2020 18:39:56 +0000

Hi guys!

As you know by my previous posts (in the Portuguese blog), I've been doing a mini-course at Udemy about data visualization in Python. This course was recommended for helping me to learn Python, so I can join the AI lab in my university ASAP.

First, I was formally presented to matplotlib.pyplot with the import command:
import matplotlib.pyplot as mpl or as plt

Next, I met the Google Colab platform, which is a Python notebook, and helped me a lot, since I can't download a Python IDE on the computer I'm currently using.

I made a line graph, with the following code (please try, it was a cute experience):

import matplotlib.pyplot as plt 

x = [1, 2] #giving x and y some values so I can plot something
y = [2, 3]

plt.plot(x, y) #plotting the graph
plt.show() #show the graph when I hit "Run"

After creating my first graph, I did the legend, so I could identify things inside what I created.

import matplotlib.pyplot as plt 

x = [1, 2, 5] #I added one more value in each variable 
y = [2, 3, 7]

plt.title("My first graph") #this is a title for my graph
plt.xlabel("Axis X") #creating labels for each axis
plt.ylabel("Axis Y")

plt.plot(x, y) 
plt.show()

Now that we learned how to do line graphs, shall we do bar graphs?

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5] #now, x represents each one of the bars
y = [2, 3, 7, 1, 0] #and y, their sizes

titulo = "Bar graph"
eixox = "Axis X"               #creating variables for the legends
eixoy = "Axis Y"

plt.title(titulo)
plt.xlabel(eixox)
plt.ylabel(eixoy)

plt.bar(x, y) #plotting the bar graph
plt.show()

Now we, with the knowledge we got about these two types of graphs, can do at least two things: compare graphs and/or unite them!

import matplotlib.pyplot as plt

x1 = [1, 3, 5, 7, 9] #odd numbers for the bars!
y1 = [2, 3, 7, 1, 0] #random numbers for their sizes: unaltered

x2 = [2, 4, 6, 8, 10] #even numbers for other bars
y2 = [5, 1, 3, 7, 4] #more random numbers, but they weren't here before

titulo = "Bar graphs"
eixox = "Axis X" #"eixo" is Portuguese for "axis"
eixoy = "Axis Y"
                             #this part you already know
plt.title(titulo)
plt.xlabel(eixox)
plt.ylabel(eixoy)

plt.bar(x1, y1)
plt.bar(x2, y2) #one and then another, but are shown together!

plt.show()

We can also unite n types of graphs! You can enter a plt.plot(x, y) in the bar graphs code, for example. But we have one more type of graph: Scatterplot, or dispersion graph. Call it by plt.scatter(x, y).

Quick note for this English version: in the Portuguese one, I've shown some images of the graphs I did so you can see how it is if you can't access Google Colab now. So I wrote thinking about the images that could be seen and now I'm adapting to DEV.

You may have seen that in the comparative graphs the colors change. Actually, these are the default colors, but you can change them to any hue you want (using mainly the color codes of plt, which you can find here), with the color tag, as in plt.scatter(x, y, color="r"), where I'm changing the color of the dots to red. You can also use the label tag to make captions for the graph, as in plt.plot(x, y, label="My line"), but using plt.legend() after it so the caption can show up in the image.

You can save your figures with plt.savefig("figurename.png"), being that "png" can be altered to "pdf" if we want a vectorized image, so it has a (really) good print quality. We have the dpi tag, which can be used to define the quality of the image. A good dpi value is, apparently, 300, and a so-so is by 72. You can use plt.savefig("figurename.png", dpi=300).

The course has a small case study with info from 1980 to 2016 about the increase in the Brazilian population, and then we're presented to the boxplot. Boxplots are box-shaped diagrams which represent variation in data per quartile. This is my current subject in Probability and Statistics, so I was very interested.

Basically, if you enter a code like this one:

import matplotlib.pyplot as plt
import random #a Python library for generating random numbers!

vetor = [] #a small vector to put values on
for i in range(100): #for a i value from (I guess) 0 to 99...
    numAleatorio = random.randint(0, 50) #random number ("número aleatório") is somewhere between 0 and 50
    vetor.append(numAleatorio) #vector receives this number so we can create the boxplot

plt.boxplot(vetor) #and then he plots the boxplot with the vector value
plt.show()

...and then press Run, it generates another image, but it's not like the other graphs, so let me explain what I know about it.

If there was something over the top (that line), that would represent values which are very different from what was asked. The above line represents the maximum that this number can be (50). Talking about 50, the main rectangle in the figure represents 50% of the obtained data. The lower line is the minimum, zero.

But where are Statistics in this? See: quartiles are fractions of a given quantity that was divided by 4. So the rectangle contains two quartiles, since 2/4 = 50%. The first line is 0%. The second (when the rectangle "begins") is 25% (1st quartile). The median (the red line) represents 50% (2nd quartile). The above line represents 75% (3rd quartile). The maximum, 100%, is the fourth quartile.

To complete the course, there was a case study about Bioinformatics, but for some reason I still haven't figured out completely, my code was resulting in many errors. I put the code on StackOverflow and I hope someone, someday, will help me to find the error. Also, if you could even look at it, I would be very thankful. Edit: I've figured it out somehow. The link is now deactivated.

I recommend this course for people who, like me, are starting to learn Python and Data Science things.
If you tried it, please leave your feedback in the comments :)

100 days of code pt. 2!

Lina Dias — Fri, 31 Jan 2020 20:27:11 +0000

2019 was a busy and confusing year. Going from school to university, ignoring prep courses or public tenders, made me feel lost and insecure about myself. A federal university is way bigger than the neighborhood school where I spent the largest 4 years of my life. An university student's lifestyle is also way different if you compare it with a second year student, for example. That, obviously, depends on the school and the university the student had enrolled.

I came into the Computer Science course without any prior (relevant) knowledge in Programming, Informatics, or even Calculus. After the year ended, I realized I didn't needed it that much.

But anyways, I was totally lost, letting things happen so I could get used to my new academic life, until the bomb came: I would have to repeat 3 subjects.

After crying a river, I woke up and realized that, if I didn't (actually) studied, I would be in the same place forever. So I studied and I think things got right after it.

While I was studying, other opportunities came, like Python Nordeste and my first 100 days of code, which I did inspired by Ana Paula from Ana no Terminal blog. It was my debut as a "tech sub-blogger", since I only posted about BTS, cute things and rants to that date. I was so proud of myself that I created LinaLina Study, my studygram which I use to register my study life.

Unfortunately, LLS is not so active now, because of some little problems that ocurred on my notebook, which I've talked about last post.

But, leaving this introduction aside, I'm only writing here to announce that I'm re-starting 100 days of code tomorrow, February 1, and ending it by May 11. This year, my main focus will be "Python and web development", and I'm going to stop searching for BTS memes for each Twitter post I make.

See you tomorrow!

Forem: Lina Dias

Why is my personal website in pure HTML?

I'm Back! + On Learning Software Engineering and Managing Failure

Number One: The Documentation Nightmare

Number Two: Scrum-Leading my Way to Hell (probably)

Number Three: (Actually) Doing some Front-end Work! Yay!

Dealing with Self-Doubt and Imposter Syndrome

In the End, Maybe it Mattered a Little

Conclusion

Contemplating Internet Inequality in Brazil

How to online study!

1. Create your own study corner

2. Entertain yourself positively

3. Use productivity apps

4. Search for interesting, useful courses

5. Define your schedule (and please stick to it)

More lectures and videos you can read or watch about this!

Code like a Fullstack girl updates #3

Code like a Fullstack girl updates #2

Code like a Fullstack girl updates #1

Going into a Data Science Python course!

100 days of code pt. 2!