Pages : | 31 |
Size : | |
File type : | HTML |
Downloads: | 197 |
Created: | 2021-05-15 |
License: | Free |
This is a free Photoshop PDF tutorial in 21 chapters and 23 pages. This course aims to give students tips and tricks in how to use efficiently Photoshop to edit your image. ...
Maya basicsThe Maya basics tutorial describes the fundamental concepts and skills for Maya that you need to work with 3D project....
Raspberry Pi TutorialThis is a free Raspberry PI PDF tutorial in 12 chapters and 43 pages. In this guide you’ll find everything you need to know about the Raspberry Pi computer, its background, purpose, system specs, the software it runs and the amazing things it is capable of. ...
Jenkins: The Definitive GuideDownload free course Jenkins: The Definitive Guide, pdf file on 417 pages by John Ferguson Smart....
Haskell tutorial for professionalsDownload free Haskell tutorial course in PDF, training file in 78 chapters and 230 pages. Free unaffiliated ebook created from Stack OverFlow contributor....
SAT/SMT by ExampleDownload free course SAT/SMT by Example, pdf file on 585 pages by Dennis Yurichev....
Tutorial Cryptography for BeginnersThis tutorial is intended to novice who wants to be familiar with lattice based cryptography and cryptosystem....
Containerized Docker Application Lifecycle with Microsoft Platform and ToolsDownload free course Containerized Docker Application Lifecycle with Microsoft Platform and Tools, pdf file on 84 pages by Cesar de la Torre....
Think Stats, 2nd Edition: Exploratory Data Analysis in PythonIf you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. ...
Think Stats: Probability and Statistics for ProgrammersIf you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. ...