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Learn to Master Python: From Beginner to Expert

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Learn to Master Python: From Beginner to Expert, available at $49.99, has an average rating of 3.85, with 430 lectures, based on 12 reviews, and has 168 subscribers.

You will learn about Code in the Python programming language. Create basic line and scatter plots with Matplotlib Customize our graphs with visuals, a title, labels, text and a legend. Optimize for intelligent apps: discover the TensorFlow mobile framework and build scientific analysis apps Machine learning goes mobile: learn how to incorporate machine learning models into Android apps And More! This course is ideal for individuals who are People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow or Absolute beginners who want to learn to code for the web in the popular Python programming language. or Anyone who wants to learn the technology that is shaping how we interact with the world around us or Beginners who want to learn how to use data science to make graphs. or Experienced programmers who want to learn a 2D plotting library for Python. or Anyone who is interested in predictive modeling for handling the stock market, weather, and text It is particularly useful for People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow or Absolute beginners who want to learn to code for the web in the popular Python programming language. or Anyone who wants to learn the technology that is shaping how we interact with the world around us or Beginners who want to learn how to use data science to make graphs. or Experienced programmers who want to learn a 2D plotting library for Python. or Anyone who is interested in predictive modeling for handling the stock market, weather, and text.

Enroll now: Learn to Master Python: From Beginner to Expert

Summary

Title: Learn to Master Python: From Beginner to Expert

Price: $49.99

Average Rating: 3.85

Number of Lectures: 430

Number of Published Lectures: 430

Number of Curriculum Items: 430

Number of Published Curriculum Objects: 430

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Code in the Python programming language.
  • Create basic line and scatter plots with Matplotlib
  • Customize our graphs with visuals, a title, labels, text and a legend.
  • Optimize for intelligent apps: discover the TensorFlow mobile framework and build scientific analysis apps
  • Machine learning goes mobile: learn how to incorporate machine learning models into Android apps
  • And More!

Who Should Attend

  • People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow
  • Absolute beginners who want to learn to code for the web in the popular Python programming language.
  • Anyone who wants to learn the technology that is shaping how we interact with the world around us
  • Beginners who want to learn how to use data science to make graphs.
  • Experienced programmers who want to learn a 2D plotting library for Python.
  • Anyone who is interested in predictive modeling for handling the stock market, weather, and text

Target Audiences

  • People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow
  • Absolute beginners who want to learn to code for the web in the popular Python programming language.
  • Anyone who wants to learn the technology that is shaping how we interact with the world around us
  • Beginners who want to learn how to use data science to make graphs.
  • Experienced programmers who want to learn a 2D plotting library for Python.
  • Anyone who is interested in predictive modeling for handling the stock market, weather, and text

We at Mammoth Interactive value input from students like you. Feel free to leave us your feedback.

This course was funded through a massively successful Kickstarter campaign.

Learn artificial intelligence, machine learning, and mobile dev with Java, Android, TensorFlow Estimator, PyCharm, and MNIST. Woah! That’s a lot of content for one course.

Use Google’s deep learning framework TensorFlow with Python. Leverage machine learning to improve your apps

Prediction Models Masterclass

By the end of this course you will have 3 complete mobile machine learning models and apps. We will build a simple ​weather prediction project, ​stock market prediction project, and ​text-response project. 

For each we will build a basic version in PyCharm, save the trained model, export the trained model to Android Studio, and build an app around model.

No experience? No problem

Do you want to learn how to visualize data? Enroll in this course to learn how to do so directly in code. 

Make 2D & 3D Graphs in Python with Matplotlib for Beginners! is suitable for coding beginners because we begin with a complete introduction to coding. Then we delve deep into using Matplotlib, a Python 2D plotting library.

In Part 1, you learn how to use 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 Matplotlib. We go over many cool features of Matplotlib that we can use for data visualization. We show you how to make line plots, scatter plots, candlestick plots. You learn how to customize the visuals of your graph and to add text and annotate graphs. And much more!

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.

Also now included in these bundles are our extra courses. If you want to learn to use other programs such as Camtasia or Sketch, you get more content than what you paid for this way!

We really hope you decide to purchase this course and take your knowledge to the next level. Let’s get started.

Enroll now to join the Mammoth community!

Course Curriculum

Chapter 1: Make Predictions with Python Machine Learning for Apps – Resources

Lecture 1: Make Predictions with Python Machine Learning for Apps – Resources

Chapter 2: Introduction to Machine Learning and Software

Lecture 1: Source Code

Chapter 3: Intro to Android

Lecture 1: Intro and Topics List

Chapter 4: Intro to Android Studio

Lecture 1: Downloading and Installing Android Studio

Lecture 2: Exploring Interface

Lecture 3: Setting up an Emulator and Running Project

Chapter 5: Intro to Java

Lecture 1: Intro to Language Basics

Lecture 2: Variable Types

Lecture 3: Operations on Variables

Lecture 4: Array and Lists

Lecture 5: Array and List Operations

Lecture 6: If and Switch Statements

Lecture 7: While Loops

Lecture 8: For Loops

Lecture 9: Functions Intro

Lecture 10: Parameters and Return Values

Lecture 11: Classes and Objects Intro

Lecture 12: Superclass and Subclasses

Lecture 13: Static Variables and Axis Modifiers

Chapter 6: Intro to App Development

Lecture 1: Intro To Android App Development

Lecture 2: Building Basic UI

Lecture 3: Connecting UI to Backend

Lecture 4: Implementing Backend and Tidying UI

Chapter 7: Intro to ML Concepts

Lecture 1: Intro to ML

Lecture 2: Pycharm Files

Chapter 8: Intro to Pycharm

Lecture 1: Intro and Topics List

Lecture 2: Learning Python with Mammoth Interactive

Chapter 9: Introduction

Lecture 1: Downloading and Installing Pycharm and Python

Lecture 2: Support for Python Problems or Questions

Lecture 3: Exploring Pycharm

Chapter 10: Python Language Basics

Lecture 1: Intro to Variables

Lecture 2: Variables Operations and Conversions

Lecture 3: Collection Types

Lecture 4: Collections Operations

Lecture 5: Control Flow If Statements

Lecture 6: While and For Loops

Lecture 7: Functions

Lecture 8: Classes and Objects

Chapter 11: Intro to Tensorflow

Lecture 1: Intro

Lecture 2: Installing TensorFlow

Lecture 3: Topics List

Lecture 4: Importing Tensorflow to Pycharm

Lecture 5: Constant Nodes and Sessions

Lecture 6: Variable Nodes

Lecture 7: Placeholder Nodes

Lecture 8: Operation nodes

Lecture 9: Loss, Optimizers, and Training

Lecture 10: Building a Linear Regression Model

Lecture 11: Source Files

Chapter 12: Machine Learning in Android Studio Projects

Lecture 1: Introduction to Level 2

Chapter 13: Tensorflow Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Setting up Prebuilt Estimator Model

Lecture 4: Evaluating and Predicting with Prebuilt Model

Lecture 5: Building Custom Estimator Function

Lecture 6: Testing the Custom Estimator Function

Lecture 7: Summary and Model Comparison

Lecture 8: Source Files

Chapter 14: Intro to Android Machine Learning Model Import

Lecture 1: Intro and Demo

Lecture 2: Topics List

Lecture 3: Formatting and Saving the Model

Lecture 4: Saving the Optimized Graph File

Lecture 5: Starting Android Project

Lecture 6: Building the UI

Lecture 7: Implementing Inference Functionality

Lecture 8: Testing and Error Fixing

Lecture 9: Source Files

Chapter 15: Simple MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List and Intro to MNIST Data

Lecture 3: Building Computational Graph

Lecture 4: Training and Testing the Model

Lecture 5: Saving and Freezing the Graph for Android Import

Lecture 6: Setting up Android Studio Project

Lecture 7: Building the UI

Lecture 8: Loading Digit Images

Lecture 9: Formatting Image Data

Lecture 10: Making Prediction Using Model

Lecture 11: Displaying Results and Summary

Lecture 12: Simple MNIST – Mammoth Interactive

Chapter 16: MNIST with Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Building Custom Estimator Function

Lecture 4: Building Input Functions, Training, and Testing

Lecture 5: Predicting Using Our Model and Model Comparisons

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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