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Joseph Santarcangelo and Ramesh Sannareddy

Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

In this mini-course you will demonstrate what you’ve learned in the Python Basics* course and apply your Python skills to a real-world project for your final assignment. You will be introduced to unit testing and will develop the skills needed to create functions and unit tests, run the unit tests, and package the files in a standard Python Package.

Hands-on labs provide practical application of the project work you’ll be performing in the Peer-graded Final Assignment.

At the end of this project, you will have the skills to test your Python code, build and run unit tests, and package the Python application for distribution.

PRE-REQUISITE: *Python Basics course from IBM is a pre-requisite for this project course. Please ensure before taking this course you have either completed the Python Basics course from IBM or have equivalent proficiency in working with Python and data.

NOTE: This course is designed for the learner to apply prior Python knowledge. It is not intended to teach you Python and includes minimal instructional content.

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What's inside

Learning objectives

  • Demonstrate python basic skills for developing ai powered applications.
  • Describe the purpose of unit testing and packaging.
  • Test your python code.
  • Create a python package.
  • After completing this course, you will be able to:
  • Expand your practical experience using ibm watson apis.

Syllabus

Module 1: Course Introduction
Module 2: Unit Testing and Packaging
Module 3; Peer-graded Final Project: Build, Test and Package your Python Application

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Offers hands-on labs that provide practical experience of the project work
Covers the fundamentals of unit testing and packaging in Python
Provides an opportunity to expand practical experience using IBM Watson APIs
Assumes prior knowledge of Python and is not suitable for beginners

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Reviews summary

Involving and helpful python course

According to students, this engaging Python course is understandable and helpful for learners. Its content is well-received, and it includes helpful assignments and involving lectures.
Assignments help with understanding the material
Easy to understand and engaging lectures
"I found the course really understandable"
"I really appreciate the efforts and involvement in delivering the content."

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 Python for AI & Development Project with these activities:
Develop a Python application that solves a real-world problem
Apply your Python skills to a real-world scenario by creating a practical application.
Browse courses on Problem Solving
Show steps
  • Identify a real-world problem that can be solved using Python.
  • Brainstorm a solution and design the application architecture.
  • Implement the application using Python.
  • Test the application thoroughly.
  • Deploy the application to a cloud platform or other hosting environment.
Discuss Python unit testing and packaging with peers
Engage with other learners to share knowledge and insights about unit testing and packaging in Python.
Browse courses on Unit Testing
Show steps
  • Join a study group or online forum for Python learners.
  • Initiate or participate in discussions about unit testing and packaging.
  • Share your experiences and learn from others.
Solve Python coding challenges
Practice your Python coding skills by solving a variety of challenges online.
Show steps
  • Find a website or platform that offers Python coding challenges.
  • Choose a challenge that is appropriate for your skill level.
  • Solve the challenge and test your solution.
  • Review your solution and identify areas for improvement.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete Python tutorials on unit testing and packaging
Supplement your understanding of unit testing and packaging by following tutorials from reputable sources.
Browse courses on Unit Testing
Show steps
  • Identify reputable websites or platforms that offer Python tutorials.
  • Search for tutorials on unit testing and packaging.
  • Follow the tutorials and complete the exercises.
  • Review your work and identify areas for further exploration.
Attend a workshop on Python unit testing and packaging
Supplement your online learning with an immersive workshop led by industry experts.
Browse courses on Unit Testing
Show steps
  • Research and identify reputable workshops on Python unit testing and packaging.
  • Register for a workshop that aligns with your schedule and learning goals.
  • Attend the workshop and actively participate in the activities.
Develop a small Python project that demonstrates unit testing and packaging
Apply your knowledge of unit testing and packaging by creating a practical Python project.
Browse courses on Unit Testing
Show steps
  • Brainstorm a simple Python project idea that involves unit testing and packaging.
  • Design the project architecture and write the code.
  • Write unit tests for your code to ensure its correctness.
  • Package your project into a distributable format, such as a Python package.
Contribute to an open-source project related to unit testing or packaging
Gain practical experience in unit testing and packaging by contributing to open-source projects.
Browse courses on Unit Testing
Show steps
  • Identify an open-source project on GitHub or another platform that uses Python and involves unit testing and packaging.
  • Review the project's documentation and code.
  • Identify areas where you can contribute, such as adding unit tests or improving packaging.
  • Create a pull request with your contributions.

Career center

Learners who complete Python for AI & Development Project will develop knowledge and skills that may be useful to these careers:
AI Engineer
AI Engineers design, develop, and implement AI solutions. This course provides a solid foundation in Python and introduces AI techniques, which are essential for success in this role.
Machine Learning Engineer
Machine Learning Engineers apply machine learning techniques to solve real-world problems. This course provides a solid foundation in Python, which is widely used in machine learning, and introduces AI concepts to help you succeed in this field.
Full-Stack Developer
Full Stack Developers are responsible for both the front-end and back-end of software applications. This course can help you develop the necessary skills in Python and AI to work on both the front-end and back-end of AI-powered applications.
Data Scientist
Data Scientists use their knowledge of AI and Python programming to extract insights from large datasets. This course can help build a foundation in Python and AI techniques, which are essential for success in this role.
Software Developer
Software Developers design, build, and maintain software applications. This course can help you build a foundation in Python, which is widely used in software development, and introduces AI concepts to help you develop innovative software solutions.
Software Engineer
Software Engineers design and build software systems. Having a strong foundation in Python and an understanding of AI techniques is highly valued in this role, as these skills can help you develop innovative and efficient software solutions. This course can help you gain the necessary skills to excel as a Software Engineer.
Cloud Architect
Cloud Architects design and manage cloud computing systems. Having a strong foundation in Python and an understanding of AI techniques can help you develop and implement AI-powered cloud solutions.
Cybersecurity Analyst
Cybersecurity Analysts protect computer systems and networks from security breaches. Having a strong foundation in Python and an understanding of AI techniques can help you develop and implement effective cybersecurity solutions.
Data Analyst
Data Analysts use data to make informed decisions. Having a strong foundation in Python and an understanding of AI techniques can help you analyze data more efficiently and effectively, making you a valuable asset in this role.
IT Consultant
IT Consultants provide advice and support to organizations on the use of technology. Having a strong foundation in Python and an understanding of AI techniques can help you provide expert advice on the implementation of AI solutions.
Business Analyst
Business Analysts use data to identify business problems and opportunities. Having a strong foundation in Python and an understanding of AI techniques can help you analyze data more efficiently and effectively, making you a valuable asset in this role.
Technical Writer
Technical Writers create documentation for software and other technical products. Having a strong foundation in Python and an understanding of AI techniques can help you write clear and concise documentation for AI-powered applications.
Product Manager
Product Managers are responsible for the development and launch of new products. Having a strong foundation in Python and an understanding of AI techniques can help you develop innovative products that meet the needs of the market.
Project Manager
Project Managers plan, execute, and close projects. Having a strong foundation in Python and an understanding of AI techniques can help you manage projects more efficiently and effectively, especially in the development of AI-powered solutions.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help you build a foundation in Python, which is widely used in quantitative finance, and introduces AI concepts to help you develop more sophisticated models.

Reading list

We've selected 11 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 Python for AI & Development Project.
Provides a comprehensive introduction to Python, including coverage of basic syntax, data types, control flow, functions, and object-oriented programming. It also includes hands-on projects that help learners apply their knowledge to real-world problems.
Teaches practical Python skills for automating everyday tasks, such as web scraping, data analysis, and file manipulation. It valuable resource for learners who want to apply their Python knowledge to real-world problems.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data cleaning, data manipulation, data visualization, and machine learning. It valuable resource for learners who want to use Python for data-driven projects.
Provides a comprehensive introduction to machine learning with Python, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for learners who want to use Python for machine learning projects.
Provides a comprehensive introduction to deep learning with Python, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for learners who want to use Python for deep learning projects.
Provides a comprehensive introduction to Python for scientists, covering topics such as data analysis, scientific computing, and visualization. It valuable resource for learners who want to use Python for scientific research.
Provides a comprehensive introduction to Python for finance, covering topics such as data analysis, risk management, and investment automation. It valuable resource for learners who want to use Python for financial applications.
Provides a comprehensive introduction to Python for web development with Django, covering topics such as web application development, database programming, and user authentication. It valuable resource for learners who want to use Python for web development projects.
Provides a comprehensive introduction to Python for data science, covering topics such as data analysis, data visualization, and machine learning. It valuable resource for learners who want to use Python for data science projects.
Provides a comprehensive introduction to Python for machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for learners who want to use Python for machine learning projects.
Provides a comprehensive introduction to Python for finance, covering topics such as data analysis, risk management, and investment automation. It valuable resource for learners who want to use Python for financial applications.

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