Efficient Application Development with Python3 for Beginners

Packt Publishing

4.3

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Packt Publishing

Python is an open-source community-supported, a general-purpose programming language that, over the years, has also become one of the bastions of data science. Thanks to its flexibility and vast popularity that data analysis, visualization, and machine learning can be easily carried out with Python.

With this application development course with Python 3, you'll first learn about variables, control flow statements & much more make use of them in Python programs. Then you will learn to use Python's advanced data structures such as lists and dictionaries. Then you will get a hands-on project building such as build a game that consists of a deck of playing cards, Dice-Rolling Simulator in Python, Building Architectural Marvels & much more. Moving further, you'll learn to troubleshoot your python application where you can quickly detect which lines of code are causing problems, and fix them quickly without going through 300 pages of unnecessary detail.

Contents and Overview

This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Begin Python Programming in 7 Days will get you started by setting up your environment and the tools you need to start programming in Python. You will be learning about variables and operators and how to make use of them in Python programs. You will learn all about control flow statements and loops in Python and you will be using them in your programs to solve your coding problems. Then you will learn to use Python's advanced data structures such as lists and dictionaries. You will be able to organize in functions and save time coding by writing code that can be reused. Then, you will learn about Python modules and how to make use of them. On the last day, you will start interacting with files using Python code. The course will give you a strong entry point into programming in general and programming in Python in particular.

The second course, Python By Example explores Python basics, data structures, and algorithms. We'll build a die rolling simulator to see how to use Python dictionaries, loops, functions, and control statements. Then, we will see how we can develop dictionaries that contain other dictionaries to build complex data structures. Next, we will use a modular approach to build a game that consists of a deck of playing cards. We will use object-oriented (OOP) Python classes to do so. We will display the playing cards both in a textual form, which we create, as well as via image files. This will lead to our displaying card images in a graphical form using Python's built-in Tkinter package. In the next part, we will use multiple inheritances with OOP classes. While the Java and C# programming languages are limited to only single inheritance, Python classes can inherit from multiple classes. You will learn how to use multiple inheritances with Python. You will also build Graphical User Interfaces (GUIs). We will use Python's built-in Tkinter package and delve more deeply into GUI programming. By the end of this video tutorial, you will have built some useful utilities using Python. Python is very strong at searching directory folders, replacing words within modules, and much more. You will find these utilities useful in your everyday work as a developer.

The third course, Troubleshooting Python Application Development takes you through a structured journey of performance problems that your application is likely to encounter, and presents both the intuition and the solution to these issues. You'll get things done, without a lengthy detour into how Python is implemented or computational theory. Quickly detect which lines of code are causing problems, and fix them quickly without going through 300 pages of unnecessary detail.

About the Authors:

Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and cloud computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feed back into how our AI generates content. Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first-hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with High Dimension, IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye.In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform to learn deeply about reinforcement learning and supervised learning topics in a commercial setting. Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean's List, and received awards such as the Deutsche Bank Artificial Intelligence prize.

Burkhard is a professional software test automation designer, developer, and analyst. He has more than 18 years' professional experience working for several software companies in California, USA. He currently works as an independent Python consultant from New York. He is the author of the Python GUI Programming Recipes using PyQt5 Packt video course. He is the author of Python GUI Programming Cookbook, First and Second Edition. This book is also available as a Packt video course. He is also the author of the Python Projects Packt video course. In his professional career, he has developed advanced in-house testing frameworks written in Python 3. He has also created advanced test automation GUIs in Python, which highly increased the productivity of the software development testing team. When not dreaming in Python code, he reads programming books about design, likes to go for walks, and reads classical poetry.

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What's inside

Syllabus

Begin Python Programming in 7 Days

This video provides an overview of the entire course

Illustrate the main tenets of programming in Python: the language and the editors.

Learn what Python is
Learn how to get started with Python
Create Python code

Show what a command line is and how to use it.

Learn what REPL is
Learn what IPython is

Demonstrate how we can write our own Python program and run it.

Write your first Python program
Run it

Demonstrate the basic syntax of Python.

Work with numbers
Work with strings
Work with lists

This video is your assignment for Day 1

Take a look at the assignment and try solving it on your own before the next section

Show how variables are used and created in Python.

Understand variables
Create variables

Demonstrate the uses of variables.

Assign values to variables
Check the type of variables

Show how operators are defined in Python.

Learn what operators are
Explore some of the useful Python operators

Show how operators are used in Python.

Chain operators and use parenthesis to group them
Assign expressions to variables

This video is your assignment for Day 2

Take a look at the assignment and try solving it on your own before the next section

Define control statements.

Learn about control statements
Explore the if statement
Explore the if else statement

Show how we can use control statements in practice.

Use control statements
Use the if statement to detect input
Use elif and else to detect input

Define loops.

Understand what loops are
Understand the while loop
Learn about the for loop

Show how we can use loops in practice.

Learn how to use loops
Loop through a list with a while loop
Loop through a list with a for loop

This video is your assignment for Day 3

Take a look at the assignment and try solving it on your own before the next section

A deeper dive into Python lists.

Learn what we can do and cannot do with lists
Go through nested lists

Show how we can operate on lists and call its methods.

Index lists with slices
Differentiate between extending and appending
Go through length, sort, and reverse

Introduce the concept of dictionary.

Learn what a dictionary is
Create a dictionary

Show how we can operate on dicts and call methods.

Loop through the items of a dictionary
Remove keys and add new keys

This video is your assignment for Day 4

Take a look at the assignment and try solving it on your own before the next section

This video is an introduction to functions.

Learn what functions are
Declare functions
Return values

In this video, we will be looking into the usage of functions in your code.

Use functions
Smartly put code in functions

This video is all about scope of variables.

Learn what scoping is
Learn how Python handles scoping

Go through an example.

Global variables versus local variables
Go through the demonstration

This video is your assignment for Day 5

Take a look at the assignment and try solving it on your own before the next section

This video will show you the importance of Python modules.

Learn what modules are
Learn why to use modules
Create modules

In this video, we will be using third-party Python modules.

Learn where to find third-party modules
Understand pip

Learn about compiled Python files.

Go through Python bytecode
Take a look at bytecode

In this video, we will be using Python packages.

Explore some modules that come with Python
Go through collections, string, and others

This video is your assignment for Day 6

Take a look at the assignment and try solving it on your own before the next section

Understand how to read text from a file.

Path handling in python
Read files into a variable
Read lines into a variable

In this video, we will be writing text to a file.

Merge strings in Python
Understand filesystem mechanics
Write text into a file

See how exceptions are handled.

Learn what might go wrong
Learn how to catch errors

This video is your assignment for Day 7

Take a look at the assignment and try solving it on your own

This video will give you an overview about the course.

We wish to learn the powerful and popular Python programming language in a fun way.

Build a simple dice rolling simulator
Enhance the simulator using functions
Add dictionaries and become more complex

We like to use complex data structures to store and use our data.

Start using a dictionary
Nest another dictionary within the dictionary
Nest many more dictionaries into dictionaries

We like to understand how Python generator functions work and what they can be used for.

Build a generator function.
Compare a generator to a regular function
Yield the results using next and for loops

We like to understand how to iterate over Python data collections. There are several different collections, like tuples, lists, dictionaries and sets.

Use tuples
Use lists and sets
Use several Python comprehensions

We want to build our own game of playing cards.

Create cards in a simple textual form
Use the random module to shuffle the deck
Advance to using OOP classes

We like to advance our game of playing cards using graphical image files.

Start simple using gif image files
Make our code object-oriented.
Use tkinter to display the graphical cards

We find some nice free image files of playing cards on the internet but they are either too large or too small so we want to resize them to fit our application.

Install Pillow and use the Image module
Convert Unicode cards into 16-bit surrogate pairs.
Use tkinter to display png and Unicode cards

In the previous videos we explored several ways how to create textual playing cards, order, shuffle and display them. We also learned how to resize graphical image card files. Now we want to use them to play a card game.

Reuse some of our previous code
Build the game logic
Create a new tkinter game GUI

We want to learn how to program object-oriented.

Explore Python’s Duck typing
Advance to using objects
Inherit from abstract classes

We want to become great programmers.

Start to understand OOP
Understand single inheritance
Move forward to multiple inheritance

We want to apply what we have learned. We are building our first building using software.

Use single inheritance
Use multiple inheritance
Create a Cathedral

We are building a Greek classic temple.

Use Unicode to represent the floorplan and frontview
Use multiple inheritance
Mix in extra functionality

We want to learn how to build a GUI.

Use Python’s tkinter module to build a GUI
Add widgets to the GUI
Create a callback function

We want to add many widgets to our GUI.

Use a loop to add the widgets
Use lambda to pass variables to callback functions
Add Progress Bar and Paned Window controls

We want to use several layered Notebook tab controls. Out of the box, tkinter does not provide this widget so we build our own.

Use frames and notebooks together
Create and remove buttons dynamically
Mimic a notebook tab click event

We want to make our GUI look good and modern.

See ways how to control the GUI size
Add several colors to different widgets
Use ttk style element functionality

We want to search the directories on our hard drive. We want to find certain files and get a count of folders and files.

Use Python’s OS module
Define our search start using OS functions
Use OS walk to walk an entire directory tree

We want to search many of our Python modules and rename code within all of them.

Create backups of our code modules
Generate Python class modules via code
Rename all instances of our classes

We want to administer our Windows systems. We also want to collect statistics of CPU, memory, disk io, and other resources.

Use the psutil Python module
Collect data similar to task manager
Collect data over time

We want to automate some of the tedious daily tasks. We have lots of Excel documents and manually have to open, read and close them to collect summary data. We want to automate this process.

Use the OpenPyXL Python module
Create Excel documents with data
Open, read, and summarize data from many Excel documents

This video gives glimpse of the entire course.

Time is of essence and timeit is your tool. In this video we explore timeit.

Understand what is timeit
Set up our timing experiment
Run our timing experiment

In this video, we will look at profile module and understand where time is spent.

Understand what is profiling
Understand how Profiling our Fibonacci sequence generator is done
Profile the sequence generator using the least recently used cache

In this video we will explore and understand tips and tricks which will allow us to track time more precisely using cProfile.

Understand the difference between cProfile vs profile
Explore and create artificially slowed functions
Understand profiling using cProfile

In this video we will understand the memory_profiler.

Explore how to go about profiling a simple function
Explore and understand how profiling manual garbage collection is done

This video is all about reducing the execution time and memory consumption.

Understand what are slots
Create classes that use slots
Inspect the performance of slots vs class dicts

In this video we will use tuples instead of lists when your data does not change.

Understand what are tuples and how to declare them
We will see by example that tuples are fasters than lists
We will understand why are they faster than lists

Save on memory consumption with generators instead of lists.

What are generators?
Why are they memory efficient?
Implementing generators

Generators are designed for a specific purpose, here is when not to use them.

when you need features from a list
when you need to iterate through a list multiple times

Chain together a series of processes so one output is another's output.

Composing two generators
Using parenthesis to define generator comprehensions

Illustrate why we need to move from Python lists to NumPy arrays

Problem 1: Memory consumption of lists for large amounts of data
Problem 2: Dynamic Typing

Show how we can use NumPy and the different ways we can create NumPy arrays

The difference between NumPy arrays and lists
Creating NumPy arrays from Python lists
Creating NumPy arrays from NumPy helpers

Show that for large n, NumPy arrays are much faster than list comprehensions

Setting up our problem with list comprehensions
Setting up its cousin in NumPy
Comparing their performance

Show how to use broadcasting - applying binary functions on arrays of varying length

What is NumPy's broadcasting?
Broadcasting: an example
How broadcasting works - three examples

Show the simple interface of numexpr and where we can use it to optimize

What is numexpr?
How to use numexpr?
Use cases of numexpr

If you have a list of URLs, serially requesting the HTML body of each page is super slow

Using requests to scrape the HTML of a web URL
Timing 10 web scraping requests

What are coroutines and how they help you request all webpages at once

What is gevent?
What are semaphores?
Creating a gevent scraper

What is event driven concurrency, and how that can speed up web scraping

What is tornado?
What is an IO Loop?
Creating a tornado based scraper

Futures and asyncio driven concurrent web scraping

What is asyncio?
await and async
Creating an asyncio based scraper

Introduce the audience to parallel programming concepts.

What is parallel processing?
Embarrassingly parallel and less embarrassingly parallel
The global interpreter lock of Python

Show how the decorate-sort-undecorate pattern can be beaten

The decorate-sort-undecorate pattern
Beating the DSU pattern with a sort key

Show how we can use Pool to achieve multiprocessing

What is Pool?
Our first process Pool
Asynchronous process Pools

In this video we will understand how we can stop processes from interfering with each other using locks.

We will be using multiprocessing.Value to share variables
Why does it not add up?
Using a lock to remove overwrites

This video covers the effects of many processes.

Using the logging module
Creating the right logger format for multiprocessing
Logging multi-processes

This video is focused on understanding how to copy and clone objects the right way.

Identify the wrong object instance
Use the correct object clone

This video will show us how to mini-classes of Python: namedtuples

Learn about mini-classes of Python

In this video we will understand how to create smart values with static methods and properties.

Create smart values with static methods and properties

In this video we will be understanding how to compare two different objects.

Understanding how to compare two different objects

In this video we will explore how to do real OOP by implementing abstract base classes in Python.

Do real OOP by implementing abstract base classes in Python

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Starts with the fundamentals of Python programming, including variables, operators, control flow statements, and loops, which provides a solid foundation for beginners

Explores Python's advanced data structures like lists and dictionaries, which are essential for efficient data manipulation and organization in Python applications

Includes hands-on projects like building a card game and a dice-rolling simulator, which allows learners to apply their knowledge and develop practical skills

Covers troubleshooting techniques for Python applications, which helps developers quickly identify and fix code issues, improving their debugging skills

Teaches how to build graphical user interfaces (GUIs) using Python's built-in Tkinter package, which is useful for creating interactive desktop applications

Explores performance optimization techniques using modules like NumPy and numexpr, which are valuable for improving the efficiency of Python applications

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Reviews summary

Python 3 basics to application development

According to learners, this course offers a comprehensive introduction to Python 3, progressing from basic syntax to more advanced application development concepts like OOP, GUIs, and even performance troubleshooting. Many highlight the hands-on projects as a major strength, providing practical application of the concepts. While the initial sections are seen as well-paced for beginners, some reviewers find the later topics cover significant ground very quickly, which might require additional external resources or prior knowledge for deeper understanding. The course is generally well-regarded for its breadth, but depth varies across topics.

Instructor provides clear explanations overall.

"The instructor is very clear in explaining the basic concepts, which is crucial for beginners."

"I found the explanations easy to follow, especially in the early and intermediate modules."

"While the pace increases, the explanations themselves are generally concise and to the point."

The initial sections are beginner-friendly.

"As someone completely new to Python, the first part of the course was a perfect introduction. Very clear explanations."

"It starts slow and builds up, which is exactly what I needed as a beginner."

"The 'Begin Python Programming in 7 Days' section is great for getting started with the basics."

Practical examples and projects reinforce learning.

"The hands-on coding and projects are the strongest part of the course for me, they really helped solidify my understanding."

"Building the game and working with the GUI module in Tkinter was a great way to see Python applied."

"I found the utility projects, like file searching and Excel automation, immediately useful for my work."

Provides a broad overview of many Python topics.

"This course covers a surprising amount of ground, from the absolute basics to more advanced topics like performance and concurrency."

"I appreciated that it didn't just stop at the fundamentals but went into OOP, GUIs, and even troubleshooting techniques."

"It's essentially three courses in one, which gives a really wide perspective on Python development."

Deeper understanding may require extra resources.

"I definitely needed to supplement with other tutorials and documentation, especially for the troubleshooting and concurrency parts."

"While it introduces many topics, you won't become an expert from this course alone; it's more of a high-level tour for later sections."

"It provides a good starting point, but mastering the later concepts requires further practice and study elsewhere."

Later topics move very quickly.

"While the breadth is good, the later sections on performance and multiprocessing felt rushed. It was hard to keep up."

"I felt like the complexity ramped up too fast after the intermediate topics, making it difficult to fully grasp."

"Some modules cover very advanced topics in a single video, requiring me to pause constantly and look up external info."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Efficient Application Development with Python3 for Beginners with these activities:

Review Python Basics

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Reinforce foundational Python concepts like variables, data types, and operators to ensure a solid base for application development.

Browse courses on Python Basics

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Review online tutorials and documentation.
Complete basic Python exercises on platforms like HackerRank or LeetCode.
Write simple programs to practice using variables, operators, and control flow.

Read 'Python Crash Course'

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Gain a practical understanding of Python through hands-on projects, reinforcing the concepts taught in the course.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

Show steps

Read the book cover to cover.
Complete the exercises at the end of each chapter.
Work through one or more of the projects in the book.

Practice Python Data Structures

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Sharpen your skills in using Python's data structures (lists, dictionaries, tuples, sets) through targeted exercises.

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Solve data structure problems on LeetCode or HackerRank.
Implement common data structure algorithms from scratch.
Practice using list comprehensions and dictionary comprehensions.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Build a Simple GUI Application

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Apply your Python knowledge by creating a graphical user interface (GUI) application using Tkinter, reinforcing your understanding of event handling and GUI design.

Show steps

Choose a simple application idea (e.g., a calculator, a to-do list).
Design the GUI layout using Tkinter widgets.
Implement the application's functionality and event handling.
Test and debug the application.

Document Your Learning Journey

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Solidify your understanding by creating a blog or a series of posts documenting your learning process, challenges, and solutions encountered during the course.

Show steps

Create a blog or use a platform like Medium.
Write about the concepts you're learning in each module.
Share code snippets and examples.
Reflect on your learning experience.

Contribute to a Python Project

Show steps

Deepen your understanding of Python development by contributing to an open-source project, gaining experience with version control, collaboration, and real-world coding practices.

Show steps

Find a Python project on GitHub that interests you.
Read the project's contribution guidelines.
Identify a bug or feature to work on.
Submit a pull request with your changes.

Read 'Effective Python'

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Learn advanced Python techniques and best practices to write more efficient and maintainable code.

View Effective Python: 125 Specific Ways to Write... on Amazon

Show steps

Read the book cover to cover.
Try out the examples in the book.
Apply the tips to your own projects.

Career center

Learners who complete Efficient Application Development with Python3 for Beginners will develop knowledge and skills that may be useful to these careers:

Python Programmer

A Python Programmer writes, tests, and debugs code using the Python programming language. This course, focusing on efficient application development with Python 3, is directly relevant. The course covers the fundamentals of Python, including variables, data structures, and control flow. The hands-on projects, such as the dice rolling simulator and card game, provide practical coding experience. The course also teaches how to troubleshoot Python applications. This course helps Python Programmers to obtain practical skills in application development and troubleshooting.

See salaries and explore the career path for Python Programmer

Junior Python Developer

A Junior Python Developer writes and maintains code using primarily the Python programming language. This course, with its focus on efficient application development with Python 3, helps build a strong foundation for this career. The course covers variables, control flow statements, and advanced data structures, all essential for a Python developer. Furthermore, the hands-on projects, such as building games and simulators, provide practical experience. This course also teaches troubleshooting Python applications, which is useful for quickly resolving code issues. Anyone aspiring to be a Python Developer should take this course as it helps to enter the world of Python application development and prepares learners to handle real-world coding challenges.

See salaries and explore the career path for Junior Python Developer

Software Developer

A Software Developer is involved in the entire lifecycle of software creation from design to implementation and testing. This course helps build a foundation for a software developer looking to specialize in Python applications. This course covers variables, control flow statements, and Python's advanced data structures. The hands-on projects, such as the game and architectural marvel building, offer practical experience. The troubleshooting modules provide insight into identifying and quickly resolving code-related issues. Software Developers seeking to learn Python application development find this course to be a valuable starting point.

See salaries and explore the career path for Software Developer

Game Developer

A Game Developer creates video games for various platforms, and Python can be used for game scripting and prototyping. This course helps build foundational knowledge for game developers interested in using Python. The course includes hands-on project of building a game involving a deck of playing cards. The course may also be useful for developing game tools and utilities in Python. Aspiring game developers benefit from this course by gaining Python skills applicable to game development tasks.

See salaries and explore the career path for Game Developer

Quality Assurance Engineer

A Quality Assurance Engineer tests software to ensure it meets quality standards, and Python is often used for test automation. This course helps build a foundation for QA engineers to use Python for writing automated tests. The course covers Python basics, data structures, and control flow, which are all helpful for writing test scripts. The course provides familiarity with Python, which is helpful for test automation tasks, particularly the ability to troubleshoot Python apps. QA Engineers should consider this course to learn Python for automation.

See salaries and explore the career path for Quality Assurance Engineer

DevOps Engineer

A DevOps Engineer manages and automates software deployment and infrastructure, and Python is a common language used for scripting and automation in DevOps. This course may be useful to DevOps engineers looking to learn Python for automation. The course covers Python basics, data structures, control flow, and file handling, which are useful for writing automation scripts. The troubleshooting section may also helps in debugging automation scripts. This course may provide a good starting point for DevOps engineers to learn Python for infrastructure automation.

See salaries and explore the career path for DevOps Engineer

Embedded Systems Engineer

An Embedded Systems Engineer develops software for embedded systems. This course may be useful to a Embedded Systems Engineer as Python is often used to write programs. The course covers Python basics, data structures, and control flow, which are important for software development. Embedded System Engineers may find this course useful to learn Python.

See salaries and explore the career path for Embedded Systems Engineer

Software Engineer

A Software Engineer designs, develops, and tests software applications. This course may be useful to a software engineer looking to expand their skillset into Python application development. The course covers core Python concepts, including variables, data structures, and control flow statements. The hands-on projects, such as building a card game and dice-rolling simulator, provide practical application of these concepts. More experienced engineers may find the section on troubleshooting Python applications particularly useful for quickly identifying and resolving performance issues. This course may allow software engineers to enhance their coding skills by diving into Python application development.

See salaries and explore the career path for Software Engineer

Automation Engineer

An Automation Engineer designs and implements automated systems, often using scripting languages like Python. This course may be useful to an automation engineer looking to use Python for scripting and automation tasks. The course covers Python basics, data structures, and control flow statements. The course also touches on file handling, which may be useful for automation scripts that read and write to files. Additionally, the troubleshooting section may assist in debugging automation scripts. Automation Engineers can use this course to enhance their coding skills.

See salaries and explore the career path for Automation Engineer

Backend Developer

A Backend Developer works on the server-side logic and databases that power web applications, and Python is a common language used for backend development. This course may be applicable to backend developers as it introduces them to Python fundamentals, data structures, and control flow. The course also includes building projects and GUI development with Tkinter. The course is useful for backend developers to understand the basics of Python for backend development tasks. Backend developers should consider this course to expand their knowledge base to include Python basics.

See salaries and explore the career path for Backend Developer

Full-Stack Developer

A Full Stack Developer works on both the front-end and back-end of web applications. This course may be useful to full stack developers who want to add Python to their skillset. The course covers Python basics, data structures, control flow, and GUI development. The course is helpful for understanding the basics of Python for full stack development tasks. Full Stack Developers should consider this course to expand their Python skills for the backend.

See salaries and explore the career path for Full-Stack Developer

Robotics Engineer

A Robotics Engineer designs, builds, and programs robots, and Python is often used for robot control and automation. This course may be useful to robotics engineers looking to use Python for programming robots. The course covers Python basics, data structures, and control flow, which are useful for writing robot control software. Robotics Engineers may benefit by learning Python to improve their efficiency in their respective fields.

See salaries and explore the career path for Robotics Engineer

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models, and Python is the primary language used in this field. This course helps build a foundation for aspiring machine learning engineers. The course covers Python basics, data structures, and control flow. Machine Learning Engineers should take this course to learn the basics of Python.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist analyzes large datasets to extract meaningful insights and develop data-driven solutions, often leveraging programming languages like Python. This course may be applicable to aspiring data scientists, as Python is essential to this career path. This course introduces core Python programming concepts, including working with variables, control flow, and advanced data structures. The course provides a foundation for data manipulation and analysis tasks in Python. The troubleshooting section may be useful for optimizing Python code used in data science projects. Taking this course may help those venturing into the data science field build a base understanding of Python.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, processes, and analyzes data to identify trends and insights. While specialized data analysis libraries are crucial, understanding core Python is beneficial. This course may be useful for data analysts as it covers Python basics, data structures, and control flow. The course may also be helpful as a base to move on to learning pandas and numpy for data analysis. Aspiring Data Analysts benefit from this course by gaining a basic understanding of Python to work with data.

See salaries and explore the career path for Data Analyst

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Efficient Application Development with Python3 for Beginners.

Effective Python

Save

Valuable resource for intermediate Python developers looking to improve their coding skills and write more efficient, maintainable, and Pythonic code. It presents 90 specific tips and best practices, covering a wide range of topics from data structures and functions to concurrency and debugging. This book is best used as additional reading to deepen your understanding of Python's nuances and best practices.

Effective Python: 125 Specific Ways to Write Better...

Kindle Edition

Python Crash Course, 2nd Edition

Save

Provides a fast-paced, thorough introduction to Python programming. It's particularly useful for beginners as it focuses on practical application through project-based learning. The book covers fundamental concepts and guides you through building real-world applications, making it an excellent resource for solidifying your understanding of Python and preparing you for more advanced topics.

Python Crash Course, 2nd Edition: A Hands-On,...

Paperback

Python Crash Course, 2nd Edition: A Hands-On,...

Kindle Edition

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