Caleb Curry has everything you need to know to get started as a C++ Programming Software developer / Software engineer — starting off with the super basics and then to intermediate topics.

Time indexes are below the video so you can jump to the section you want.

1:09 – Intro
9:31 – Installing g++
15:37 – C++ Concepts
22:31 – More C++ Concepts
30:48 – Using Directive and Declaration
37:33 – Variable Declaration and Initialization
40:40 – Using Variables with cout
44:46 – User Input with cin
47:57 – Conventions and Style Guides
56:23 – Intro to Functions
1:01:28 – Intro to Creating Custom Functions
1:09:05 – Pow Function
1:13:13 – Creating Custom Functions
1:22:20 – Creating Void Functions
1:29:11 – Intro to C++ Data Types
1:37:17 – Integral Data Types and Signed vs Unsigned
1:44:38 – Integral Data Types, sizeof, limit
1:49:35 – char Data Type
2:02:21 – bool Data Type
2:06:54 – Floating Point Numbers
2:15:00 – Constant const, macro, and enum
2:21:00 – Numeric Functions
2:28:37 – String Class and C Strings
2:37:47 – get line for Strings
2:40:52 – String Modifier Methods
2:47:56 – String Operation Methods
2:54:36 – Literals
2:59:42 – Hex and Octal
3:04:06 – Operator Precedence and Associativity
3:11:53 – Reviewing Key Concepts
3:17:54 – Control Flow
3:27:32 – If Statement Practice
3:32:33 – Logical and Comparison Operators
3:42:27 – Switch Statement and Enum
3:51:00 – Intro to Loops
3:58:01 – For Loops (How to Calculate Factorial)
4:05:06 – While Loop and Factorial Calculator
4:12:29 – Do While Loop
4:20:04 – Break and Continue
4:25:14 – Conditional Operator
4:29:04 – Intro to Our App
4:33:00 – Creating a Menu
4:38:11 – Creating a Guessing Game
4:45:27 – Intro to Arrays and Vectors
4:54:15 – Working with Arrays
5:04:21 – Passing Arrays to Functions
5:11:11 – Fill Array from Input
5:20:42 – Using and Array to Keep Track of Guessing
5:25:55 – Intro to Vectors
5:33:00 – Creating a Vector
5:36:39 – Passing Vectors to Functions
5:39:55 – Refactor Guessing Game to Use Vectors
5:43:47 – STL Array
5:47:47 – STL Arrays in Practice
5:51:45 – Refactor Guessing Game to Use Templatized Array
5:55:13 – Array vs Vector vs STL Array
5:01:49 – Range Based for Loop
6:07:03 – Intro to IO Streams
6:15:45 – Writing to Files with ofstream
6:24:43 – Readings from Files with ifstream
6:31:13 – Saving High Scores to File
6:39:46 – Functions and Constructors
6:47:53 – Refactoring IO to Function Call and Testing
6:54:31 – Multidimensional Arrays and Nested Vectors
6:59:29 – Const Modifier
7:04:33 – Pass by Reference and Pass By Value
7:11:41 – Swap Function with Pass by Reference
7:14:27 – Intro to Function Overloading
7:19:35 – Function Overloading Examples
7:26:22 – Default Arguments
7:33:24 – Intro to Multifile Compilation
7:40:56 – Multifile Compilation
7:48:15 – Makefiles
7:54:44 – Creating a Simple Makefile
8:01:30 – Intro to Namespaces
8:05:33 – Creating a Namespace
8:10:24 – Intro to Function Templates
8:15:24 – Creating a Function Template
8:18:40 – Overloading Function Templates
8:23:18 – Intro to Object Oriented Programming
8:30:39 – Intro to Structs
8:35:59 – Creating a Struct
8:41:48 – Classes and Object
8:49:58 – Creating a Class
8:52:45 – Working with Objects
9:00:11 – Intro to Constructors
9:05:18 – Constructors and Destructors
9:09:53 – Encapsulation
9:15:40 – Getters and Setters
9:22:47 – Static Data Members
9:29:59 – Intro to Operator Overloading
9:34:07 – Operator Overloading == and +
9:41:13 – Overloading Insert and Extraction Operators
9:49:07 – Friend Functions and Operator Overloading
9:56:14 – Class Across Files
10:03:31 – Inheritance and Polymorphism
10:08:49 – Base Classes and Subclasses Inheritance
10:16:54 – Polymorphism
10:23:15 – Conclusion

Siraj Raval explores why does a computer algorithm classify an image the way that it does? This is a question that is critical when it comes to AI applied to diagnostics, driving, or any other form of critical decision making.

In this video, he raises awareness around one technique in particular that I found called “Grad-Cam” or Gradient Class Activation Mappings.

Siraj Raval gets back to inspiring people to get into AI and pokes fun at himself.

Almost exactly 4 years ago I decided to dedicate my life to helping educate the world on Artificial Intelligence. There were hardly any resources designed for absolute beginners and the field was dominated by PhDs. In 2020, thanks to the extraordinary contributions of everyone in this community, all that has changed. It’s easier than ever before to enter into this field, even without an IT background. We’ve seen brave entrepreneurs figure out how to deploy this technology to save lives (medical imaging, automated diagnosis) and accelerate Science (AlphaFold). We’ve seen algorithmic advances (deepfakes) and ethical controversies (automated surveillance) that shocked the world. The AI field is now a global, cross-cultural movement that’s not limited to academics alone. And that’s something all of us should be proud of, we’re all apart of this. I’ve packed a lot into this episode! I’ll give my annual lists of the best ML language and libraries to learn this year, how to learn ML in 2020, as well as 8 predictions about where this field is headed. I had a lot of fun making this, so I hope you enjoy it!

Krysta Svore, principal researcher at Microsoft, demonstrates the new Microsoft Quantum Development Kit.

The Quantum Development Kit makes it easy for you to start experimenting with quantum computing now and includes: · A native, quantum-focused programming language called Q# · Local and Azure-hosted simulators for you to test your Q# solution · And sample Q# code and libraries to help you get started

In this demo, she walks through a few code examples and explains where quantum principles like superposition and entanglement apply. She explains how quantum communication works using teleportation as your first “Hello World” inspired program. And keep watching to see more complex computations with molecular hydrogen.  

Talk about cold storage.

The GitHub Arctic Code Vault is a data repository preserved in the Arctic World Archive (AWA), a very-long-term archival facility 250 meters deep in the permafrost of an Arctic mountain. The archive is located in a decommissioned coal mine in the Svalbard archipelago, closer to the North Pole than the Arctic Circle. GitHub will capture a snapshot of every active public repository on 02/02/2020 and preserve that data in the Arctic Code Vault. 

Will Kwan spent 50 days to create an AI Startup, out of the project out of Y Combinator Startup School.

You can try it out here:

I’m building a machine learning/SaaS startup. In this video, I share the results my first 50 days of full-time work, explaining my business strategy, showing the core features I designed and programmed, and summarizing what I learned from my users. I also give a overview of all the programming frameworks and API’s I used.

Siraj Raval shows off examples of machine learning apps from his students.

If you’re wondering about my stance on the recent controversies around Siraj, I recorded a Data Point about that.

Machine Learning powers almost every internet service we use these days, but it’s rare to find a full pipeline example of machine learning being deployed in a web app. In this episode, I’d like to present 5 full-stack machine learning demos submitted as midterm projects from the students of my current course. The midterm assignment was to create a paid machine learning web app, and after receiving countless incredible submissions, I’ve decided to share my favorite 5 publicly. I was surprised by how many students in the course had never coded before and to see them building a full-stack web app in a few weeks was a very fulfilling experience. Use these examples as a template to help you ideate on potential business ideas to make a positive impact in the world using machine learning. And if you’d like, be sure to reach out and support each of the students I’ve demoed here today in any way can you offer. They’ve been working their butts off. Enjoy!

Presentation notebook: