Create Arrays in Python NumPy – Learn Scientific Computing

Description

Buy Create Arrays in Python NumPy – Learn Scientific Computing Course at esyGB. You will have immediate access to the digital downloads in your account or your order email.

This course was funded by a wildly successful Kickstarter.

Learn how to use NumPy 1.12.0, the fundamental package for scientific computing with Python! This course is suitable for coding beginners because we begin with a complete introduction to coding in Python, a popular coding language used for websites like YouTube and Instagram.

You learn the basics of programming, including topics like variables, functions, and if statements. You learn about data structures such as lists, dictionaries, and sets. We cover how to use for and while loops, how to handle user input and output, file input and output. we apply our knowledge to build a fully functional tic-tac-toe game.

You learn classes, methods, attributes, instancing, and class inheritance. We make an additional Blackjack game! You learn how to solve errors that can occur when you work as a programmer.

In Part 2, you take your Python knowledge and apply it to NumPy. You learn to create and shape NumPy and 2D arrays. Learn how to resize, format, and sort arrays. Then we cover how to perform calculations within NumPy arrays. You learn about math functions, statistics, and polynomials with NumPy. And more!

What Will I Learn?

• Code in the Python 3.5 programming language.
• Make games with Python.
• Create NumPy arrays.
• Resize and manipulate arrays.
• Perform calculations, functions and statistics with NumPy.
• 22 hours on-demand video

Who is the target audience?

• Absolute beginners who want to learn to code for the web and make games in the popular Python programming language.
• Beginners who want to learn to create and manipulate arrays in NumPy.
• Anyone who wants an introduction to scientific computing and using math with NumPy.

Requirements

• Download Anaconda 4.2.0, the free data science platform by Continuum, which contains Python 3.5.2 and NumPy 1.12.0.
• Otherwise, you can download and install Python and NumPy for free online.
• Topics involve intermediate math, so familiarity with university-level math is very helpful.

Why choose Mammoth Interactive?

We prioritize learning by doing. We blend theory with practical projects to ensure you get a hands-on experience by building projects alongside your instructor. Our experienced instructors know how to explain topics clearly at a logical pace. Check out our huge catalog of courses for more content.

“The Instructor goes very in-depth about everything. This is very helpful to remember all these different things!” – KingSloth_GameStudio on The Ultimate iOS 11 Course

“I really like the approach the presenter takes – not just the technical details, but also the very human, personal development information and recommendations he provides.” – Michael on The Ultimate iOS 11 Course

“The instructor is very good at teaching. He teaches at a great pace and covers anything a beginner would need to understand (every little detail). I am already learning a lot and I just started yesterday. – Mike on Build 30 Mini Virtual Reality Games in Unity3D from Scratch

You get full lifetime access to this course for a single fee. Enroll today to join the Mammoth community!

Course Curriculum

–Introduction–

• Course Trailer! (0:23)
• Join our Forum
• Introduction to Python (2:07)

00. Basics of Programmning

• 00-01. Variables (23:46)
• 00-02. Functions (28:29)
• 00-03. ifStatements (32:19)

01. Lists

• 01-01. Introduction to Lists (31:03)

02. Loops

• 02-01. Introduction to and Examples of using Loops (39:03)
• 02-02 Getting familiar with while Loops (30:19)
• 02-03 Breaking and Continuing in Loops (30:55)
• 02-04 Making Shapes with Loops (16:28)
• 02-05. Nested Loops and Printing a Tic-Tac-Toe field (37:49)

03. Sets and Dictionaries

• 03-01 Understanding Sets and Dictionaries (25:58)
• 03-02 An Example for an Invetory List (27:16)

04. Input and Output

• 04-01 Introduction and Implementation of Input and Output (38:46)
• 04-02 Introduction to and Integrating File Input and Output (11:14)
• 04-03 An example for a Tic-Tac-Toe Game (38:09)
• 04-04 An example of a Tic-Tac-Toe Game (Cont'd) (30:49)
• 04-05 An Example writing Participant data to File (34:01)
• 04-06 An Example Reading Participant Data from File (27:38)
• 04-07 Doing some simple statistics with Participant data from File (27:22)

05. Classes

• 05-01 A First Look at Classes (42:44)
• 05-02 Inheritance and Classes (42:44)
• 05-03 An Example of Classes using Pets (24:07)
• 05-04 An Example of Classes using Pets – Dogs (17:19)
• 05-05 An examples of Classes using Pets – Cats (23:03)
• 05-06 Taking The Pets Example further and adding humans (16:33)

06. Importing

• 06-01 Introduction to Importing and the Random Library (16:15)
• 06-02 Another way of importing and using lists with random
• 06-03 Using the Time Library (12:44)
• 06-04 Introduction to The Math Library (12:44)
• 06-05 Creating a User guessing Game with Random (13:13)
• 06-06 Making the Computer guess a random number (22:47)

07. Project- BlackJack Game

• 07-01 BlackJack Game Part 1 – Creating and Shuffling a Deck (14:48)
• 07-02 Blackjack Game part 2 – Creating the player class (38:41)
• 07-03 Blackjack Game Part 3 – Expanding the Player Class (14:48)
• 07-04 Blackjack Game part 4 – Implementing a bet and win (18:23)
• 07-05 Blackjack Game part 5 – Implementing the player moves (24:24)
• 07-06 Blackjack Game Part 6 – Running the Game (Final) (37:50)

08. Error Handling

• 08-01 Getting started with error handling (23:36)

–NumPY–

• Introduction (2:58)

01. NumPY Arrays

• 01 Creating and reshaping numpy Arrays (22:54)
• 02 Creating standard numpy arrays (22:32)
• 03 Creating standard 2d arrays (15:16)
• 04 Attributes on numpy arrays (20:24)
• 05 Resizing Arrays (14:54)

02. Manipulating NumPY Arrays

• 01 Writing an Array to File and Formating Strings (30:08)
• 02 Random numbers (19:37)
• 03 Sorting in numpy (24:25)

03. Calculations and Math

• 01 Calculations within numpy arrays (23:59)
• 02 Math functions with numpy (24:34)
• 03 Integrating with numpy (24:34)
• 04 Statistics with numpy (22:07)
• 05 Polynomials (22:23)
• 06 Polynomials (Cont'd) (21:03)

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