How I Would Relearn Coding | Fast & Optimally

0:00all the knowledge that I have in

0:01programming. This is how I would relearn

0:04programming in 2026. Hello, welcome to

0:06my channel. Today, I'm going to go over

0:08how you can learn computer science and

0:09programming in 2026. If you clicked on

0:12this video, that means you either want

0:13to be a developer, learn how to build

0:15cool projects, or just learn how to code

0:17as a skill. This video is perfect

0:19because I'm going to go over all the

0:20topics that you need to know in a

0:22specific order because I do believe it

0:25will be the most frictionless and

0:26optimal. All of the knowledge in

0:27computer science and programming build

0:29on top of each other. It should actually

0:30get easier the more you learn as things

0:33make more sense. Now, the question,

0:35should you learn how to code in 2026

0:37when AI can do it in one shot? I think

0:39you should because a lot of jobs still

0:41require you to have a technical

0:42knowledge on how to write code and

0:45maintain big systems. You're like,

0:47"Who's this girl telling me how to

0:48code?" I'm Tina and I am a current big

0:51tech {slash} Fang software engineer in

0:54Silicon Valley. And I've been coding for

0:55the past 7 years in all different

0:58environments. I self-taught myself,

1:00learned with a teacher, learned in

1:01college, learned through internships,

1:03and now my job. If you want to see what

1:04it looks like as a day in my life as a

1:06software engineer, watch this video. And

1:08don't forget to subscribe for more

1:09coding and ComSci builder content. Also,

1:12follow me on TikTok and Instagram where

1:14I post cool things I build, more

1:16programming advice and content, and just

1:18more of my life as a software engineer

1:20in Silicon Valley. All the knowledge

1:22that I have in programming, this is how

1:24I would relearn [clears throat]

1:25programming in 2026. Now, I must say you

1:27cannot completely learn how to code

1:30everything and understand all of

1:31computer science within these topics

1:33because you can never truly fully

1:35understand. Even when you do learn

1:36everything, you still have new stuff

1:38that comes up every single day. But, the

1:40topics in this video will go over

1:42everything that you need to know to be

1:44self-sufficient enough. So, I'm setting

1:45this up as a 3-month study schedule

1:47separated by two parts. One, programming

1:49fundamentals, and two, data structures

1:51and algorithms. At the end, I will also

1:53go over resources, both free and paid,

1:55that I you programming and these topics.

1:58Starting off with the programming

1:59fundamentals, these are your comp sci

2:01fundamentals that you should know

2:03regardless on what you're trying to

2:05build, what language you're trying to

2:06learn, everything, all the technology in

2:08the world that you have right now is

2:10built on top of the fundamentals. There

2:12will be seven modules to this and each

2:14modules I will go over project ideas

2:17that you can implement to really lock in

2:19those concepts. The language of choice

2:21that you should learn in is Python

2:23because it has the least amount of

2:25syntax you have to overcome and you're

2:27just learning the fundamentals and

2:29Python will allow you to just write

2:31code. When I was starting out

2:32programming, I was way too focused on

2:34the syntax when in reality, once you

2:36build your project or once you use a

2:39specific language, it really doesn't

2:41take long. So, I would have rather

2:42prioritize really understanding the

2:45fundamental concepts. In module one, you

2:47should learn about language basics. So,

2:49this includes variables, primitive

2:51types, operators, input, output, control

2:54flow, loops, functions, comments, and

2:57error handling. Here are all the things

2:58that you should know from these topics.

3:00I'll put it right here on the screen.

3:01You can use this as a checker to know

3:03that you understand these. Some project

3:05ideas that will really help you

3:07understand this is calculator, guessing

3:09game, quiz game, tip calculator, unit

3:12converter, rock, paper, scissors.

3:14Basically, these projects forces you to

3:16use everything that you learned and

3:18write it. And if you don't know how to

3:19code it, then you would have to redo it.

3:21In module two, you learn object and

3:23type. This includes strings, lists,

3:25tuples, sets, dictionaries, mutability,

3:28and objects. So, some project ideas you

3:30should have for this is a contact book,

3:32grocery manager, flash cards, student

3:35grade book, and expense tracker. Again,

3:37this will force you to use the topics

3:39that you just learned. For example,

3:41implementing a contact book will force

3:43you to use object-oriented programming

3:46and having attributes for each object

3:48and functions. Module three,

3:50object-oriented programming. This is

3:51where you really get into. So, you have

3:53classes, attributes, methods,

3:56encapsulation, inheritance,

3:58polymorphism, and composition. Some

4:00project ideas for this is banking

4:03system, a pokedex, library manager,

4:05restaurant ordering, and a car

4:07dealership inventory. These projects

4:09will help you go a step further and

4:12really use the object-oriented

4:13programming knowledge, but also all your

4:15previous knowledge on objects and types,

4:18as well as computer science programming

4:20basics. This is what I mean by

4:22everything builds on top of each other

4:23because the more you learn, the more you

4:25use everything. For module four, math

4:28and computation. This includes numbers,

4:30math operators, math module, random

4:32numbers, statistics, coordinate systems,

4:35and I'll intro to algorithms. Some

4:37project ideas, a scientific calculator,

4:39but like one of these calculators, a

4:40dice simulator, Monte Carlo simulator,

4:43and a statistics calculator. Module

4:45five, software engineering principles.

4:47So, this includes software design, clean

4:50code, modular programming, testing,

4:52debugging, documentation, and Git, which

4:55is really important because you learn

4:57how to collaborate with others using

4:59code, and also how to maintain and

5:02upload your code. For this project, I

5:03would suggest you contribute to open

5:05source projects. There's so many open

5:07source projects online, and you can look

5:10at code and understand why things are

5:12written the way they are. Then module

5:14six, I would learn C++ because it

5:16teaches you how computer science

5:18fundamentals work at a lower level.

5:20Learn language basic functions,

5:22references, arrays, and strings, loops,

5:25conditional vectors, header files, and

5:28compilation. The syntax will be

5:29different, but also you will learn how

5:32memory works, which I think is really

5:34important because C++ really help you

5:37understand why and how things should

5:39run. Some project ideas, calculator,

5:41contact manager, banking CLI, Hangman,

5:44and inventory manager. Module seven,

5:47memory management in C++. So, this we

5:50have memory, pointers, dynamic memory,

5:52arrays, references, copying,

5:55constructors, memory problems, and smart

5:57pointers. The project ideas for this is

5:59a dynamic vector implementation, some

6:02string class from scratch, the allocator

6:04simulator, a text editor buffer, a

6:07simple game inventory using pointers.

6:09You might realize that when you're

6:11learning C++, things start to click more

6:13because you already learned it in

6:15Python. This is also how I learned

6:17coding at university, and it was really

6:19effective. Then, for part two, we have

6:21data structures and algorithms. This

6:23part is optional, but I highly recommend

6:25that you really understand data

6:27structures and algorithms because

6:29everything that you learn after this

6:31depends on DSA. I'm talking design

6:33pattern, code architecture, anything

6:35that has to do with writing maintainable

6:38code, anything that has to do with

6:39writing maintainable is built on top of

6:41data structures and algorithms. The

6:43topics can be summed up in foundation,

6:46arrays and strings, hash tables, linked

6:48lists, stacks and queues, trees, heaps,

6:51graphs, sorting and searching, dynamic

6:53programming, greedy algorithms, and

6:55advanced topics. A good way to

6:57understand data structures and algorithm

6:59is to build cool projects, for example,

7:01building a highly responsive contacts

7:04book or word frequency counter, file

7:06explorer or family tree for trees, a GPS

7:09navigator or a maze solver for graphs,

7:12or a student database system to to learn

7:15how sorting, searching, and hash tables

7:17work. A lot of these projects also

7:18overlap. So, as long as you integrate

7:21different DSA topics into these

7:23projects, you will be able to get

7:24hands-on experience. Now, the hard part.

7:26Where do I actually learn this? So, I

7:28gathered a bunch of resources, both paid

7:31and unpaid. I think free resources are

7:33just as effective, but to each their

7:35own, and this is not sponsored. Learn

7:37Python for free, a Harvard CS50 course.

7:40It's on YouTube. You can watch it

7:41whenever, it's as convenient. And you

7:44understand very super beginner-friendly

7:46teaches about everything that I just

7:48mentioned. If it doesn't, you can

7:50YouTube search any specific topics that

7:52you didn't cover. Then we have the rest

7:55of Helsinki Python Programming. It's

7:58practice-heavy and it focus on learning

8:01programming through Python. Then you

8:03have the Python for everyone by the

8:04University of Michigan.

8:05Beginner-friendly, slower pace than the

8:07CS50 course, and you get the materials,

8:10lecture books, and assignments. That's

8:12all for free. Paid options we have

8:14Python for everyone from Coursera and

8:17Google crash course on Python. For C++,

8:19to learn C++ for free, I recommend learn

8:22C++.com. It's one of the best C++

8:25resources and it goes over the basics

8:28like variables, functions, classes,

8:29pointers, references, templates, STL,

8:32modern C++. Then we have free Code Camp

8:35C++ courses. People really like this

8:37one. This has long-form video

8:39instructions. And then my personal

8:41favorite because I love learning on

8:42YouTube is the Cherno C++ series. He's

8:46actually one of my favorite programming

8:49YouTubers because the material that he

8:50goes through provides so much examples

8:53to really let you understand how to code

8:56in C++. Paid resources for this includes

8:58Udemy getting C++ programming, Coursera

9:01C++. Now to learn data structures and

9:03algorithms, I recommend you learn data

9:05structures in C++ because you get an

9:07extra layer on how memory works and why

9:11you're using the data structure. For

9:12example, in Python you have set, but in

9:15C++ you have unordered and ordered sets.

9:18You just have more control over your

9:20code. Good to have that when you're just

9:22starting out and trying to understand

9:23computer science fundamentals. Some

9:25courses and resources I recommend for

9:27this is the UC San Diego data structures

9:30and algorithms specialization course on

9:32Coursera, free Code DSA for beginners.

9:35He's one of my favorite YouTubers that I

9:37learned the instructions from. Then MIT

9:39Intro to Algorithms, Princeton

9:41Algorithms Part 1 and 2 on Coursera. So,

9:44after you learn the fundamentals of

9:46programming and data structures and

9:47algorithms, you're wondering, "How do I

9:49build cool projects?" So, there's so

9:51many main user interfaces that you can

9:53build. We have websites, native desktop

9:56apps, mobile apps, command line

9:58interfaces, APIs, etc. So, to continue

10:01your coding journey and you're learning

10:03how to build stuff, you kind of have to

10:06approach it as from an ad hoc basis. So,

10:09you can just learn as you go. There's so

10:11many resources online and we have AI

10:13models that can help you learn really

10:15fast. And this is a double-edged sword

10:17because some people just let AI take

10:19over when they're just starting out when

10:21it's really important to understand why

10:23the code is being written that way. And

10:25if you're about to start learning, I

10:26want to say that learning how to code

10:29requires a lot of discipline because

10:31you're going to go through moments where

10:33you're like, "What? This doesn't make

10:34sense." And you want to give up. So, you

10:36got this. Just make cool stuff. Thank

10:38you so much for watching this video. I'm

10:40actually currently building a cyberdeck,

10:42teaching myself electronics. You can

10:43check it out on Instagram with these

10:46videos. Don't forget to subscribe and

10:47support this channel because that's my

10:49number one motivator on keep posting

10:52more videos that help you become a

10:54programmer and enjoy programming as much

10:57as I do. Okay, bye.