Home Programming Rust Programming Masterclass from Beginner to Expert [Video]

Rust Programming Masterclass from Beginner to Expert [Video]

By Dr. Nouman Azam
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50+ new titles added every month on new and emerging tech
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50+ new titles added every month on new and emerging tech
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50+ new titles added every month on new and emerging tech
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  1. Free Chapter
    Introduction
About this video
In the world of programming languages, there are often tradeoffs to consider. Low-level languages such as C and C++ offer speed and control, but at the cost of memory safety. High-level languages such as Python and JavaScript prioritize safety but are less efficient in terms of power and speed. Rust, however, offers the best of both worlds. You will begin with the basics of Rust programming, including its syntax and memory safety features. As you progress, you will develop an understanding of advanced-level concepts such as generics, traits, and more. The course provides hands-on experience in solving intermediate to advanced-level problems using Rust. The course covers a range of topics, including basic Rust programming syntax, Enums, structures, rust module system, the use of external crates and publishing crates, smart pointers, commonly used data structures, advanced techniques such as macros, testing, memory allocations, and more. You will also learn some real-life applications in Rust from scratch, and efficient programming skills. Furthermore, you will understand concurrency and async programming, textual processing, directory handling, blockchain, and web programming in Rust. By the end of this course, you will become fluent in Rust programming and confidently and professionally code in the language.
Publication date:
July 2022
Publisher
Packt
Duration
20 hours 12 minutes
ISBN
9781804612187

About the Author
  • Dr. Nouman Azam

    Dr. Nouman Azam is an assistant professor at the Department of Computer Science, National University of Computer and Emerging Sciences. He has over a decade of experience in research and teaching. His research work is mainly on the exploration of machine learning techniques in application areas such as bioinformatics, text summarization, text categorization, email filtering, security, recommender systems, and medical decision making. On the theoretical side, he is interested in applying the theories of rough sets, game theory, optimization, and conflict analysis to machine learning tasks. For his master’s thesis, he applied different machine learning techniques to select important features in spam email filtering. For his doctoral thesis, he investigated the applications of machine learning techniques such as rough sets, game theory, genetic algorithms, gradient descent, and others to learn and extract data patterns. In the recent past, he has taught many fine learning-related courses at the undergraduate and graduate levels. MATLAB remains his number one choice for implementing ideas and converting code to meaningful software.

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Rust Programming Masterclass from Beginner to Expert [Video]
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