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Ramesh Sannareddy
and
Abhishek Gagneja
This mini course is intended to apply basic Python skills for developing Artificial Intelligence (AI) enabled applications. In this hands-on project you will assume the role of a developer and perform tasks including:
Read more
This mini course is intended to apply basic Python skills for developing Artificial Intelligence (AI) enabled applications. In this hands-on project you will assume the role of a developer and perform tasks including:
Read more
This mini course is intended to apply basic Python skills for developing Artificial Intelligence (AI) enabled applications. In this hands-on project you will assume the role of a developer and perform tasks including:
- Develop functions and application logic
- Exchange data using Watson AI libraries
- Write unit tests, and
- Package the application for distribution.
You will demonstrate your foundational Python skills by employing different techniques to develop web applications and AI powered solutions. After completing this course, you will have added another project to your portfolio and gained the confidence to begin developing AI enabled applications using Python and Flask, Watson AI libraries, build and run unit tests, and package the application for distribution out in the real world.
Register for this course and see more details by visiting:
OpenCourser.com/course/y8ull7/python
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What's inside
Syllabus
Python Coding Practices and Packaging Concepts
In this module, you will start with the basic difference between web applications and APIs. Next, you will learn about the application development lifecycle, from gathering requirements to maintaining the project. You will also get familiar with the best practices for coding as documented in the Python Enhancement Proposal (PEP8) style guide. You will learn about static code analysis, which is used to ensure that the code you write adheres to the coding rules. Next, you will learn how to create and run unit tests. Finally, you will learn how to create, verify, and run Python packages.
Read more
Syllabus
Python Coding Practices and Packaging Concepts
In this module, you will start with the basic difference between web applications and APIs. Next, you will learn about the application development lifecycle, from gathering requirements to maintaining the project. You will also get familiar with the best practices for coding as documented in the Python Enhancement Proposal (PEP8) style guide. You will learn about static code analysis, which is used to ensure that the code you write adheres to the coding rules. Next, you will learn how to create and run unit tests. Finally, you will learn how to create, verify, and run Python packages.
Read more
Web App Deployment using Flask
In this module, you will be introduced to the definitions of and key differences between Python libraries and frameworks for application development. You will also learn about Flask, a Python-based micro framework used for web deployment of applications. The module will also introduce development and deployment concepts, including routes, request and response objects, error handling, and decorators. After building an API with Flask, you will also learn to deploy web apps using Flask.
Creating AI Application and Deploy using Flask
In this module, you will be introduced to Embeddable Watson AI libraries. You will also have the opportunity to build two AI-based apps. The practice project will provide you with a challenge to apply your programming skills and incorporate the IBM Watson libraries to build a text-based Sentiment Analysis tool. You will be provided guidance through each step of the project. The final project, Emotion Detection based on the text input, will help you get your skills and proficiency assessed by your peers. For both projects, you will perform unit testing, static code analysis, and incorporate error handling.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
May fit for learners with a general interest in Python who want to use it for AI development
May fit for learners who need hands-on practice with tasks common in AI development
May fit for learners who would like to get experience with Watson AI libraries
May fit for learners with a basic understanding of Python who are comfortable with writing code
May fit for learners with a basic knowledge of AI concepts
May fit for learners who want to apply their Python skills to build AI solutions
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Reviews summary
Progressive python web development
Learners say this course offers engaging assignments and challenging but rewarding projects, delving into Python and Flask for web development with IBM Watson services integration. Despite some technical issues and unclear instructions in the final project, students find the overall experience largely positive and recommend it for those with interest in Python, AI, and web development.
Challenging but Rewarding
"This was actually a fun course, despite the labs being down from a long maintenance, which is why I took a star off."
Practical AI and Web Dev Skills
"The course seems promising and relevant for individuals looking to develop web applications with Python, Flask, and AI integration."
Engaging, Thought-Provoking
"The knowledge is intensive, the process is clear, and it's easy to get a complete understanding of how to create an app after completing the entire project."
Many Labs and Real-World Projects
"I really enjoyed the hands-on nature of the course. Lots of projects and practice doing stuff."
Unclear Instructions and Bugs
"The course was pretty short and didn't really live up to the name of AI & Application Development."
"The final demo project is messy since the instruction is neither aligned with previous instructions nor aligned with the final assignment when screenshots are requested to submit."
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 Developing AI Applications with Python and Flask with these
activities:
Review Basic AI Concepts
Show steps
Familiarize yourself with core AI principles and concepts to better understand the course content.
Show steps
-
Review introductory AI materials, such as books, articles, or online courses.
-
Focus on understanding the concepts of machine learning, natural language processing, and computer vision.
-
Complete practice exercises or quizzes to test your understanding.
Build a Simple Python Calculator
Show steps
Practice writing Python code by building a simple calculator project.
Browse courses on
Python Basics
Show steps
-
Design the calculator's functionality and user interface.
-
Implement the calculator's basic operations using Python.
-
Test and debug the calculator to ensure it works correctly.
Follow Flask Web Development Tutorials
Show steps
Enhance your web development skills by following online tutorials on Flask.
Show steps
-
Find reputable online tutorials on Flask.
-
Follow the tutorials thoroughly, completing any code exercises.
-
Build a simple Flask web application as a practice project.
Two other activities
Expand to see all activities and additional details
Show all five activities
Participate in Python Code Challenges
Show steps
Sharpen your Python problem-solving abilities by participating in online code challenges.
Browse courses on
Competitive Programming
Show steps
-
Find reputable online code challenge platforms.
-
Practice solving problems in various difficulty levels.
-
Participate in code challenges and aim to improve your ranking.
Develop an AI-Powered Chatbot
Show steps
Apply your Python and AI skills to create a functional AI-powered chatbot.
Browse courses on
Natural Language Processing
Show steps
-
Design the chatbot's functionality and user interface.
-
Implement the chatbot's core NLP logic.
-
Train and test the chatbot to enhance its responses.
-
Deploy the chatbot and gather user feedback.
Review Basic AI Concepts
Show steps
Familiarize yourself with core AI principles and concepts to better understand the course content.
Show steps
Show steps
Show steps
- Review introductory AI materials, such as books, articles, or online courses.
- Focus on understanding the concepts of machine learning, natural language processing, and computer vision.
- Complete practice exercises or quizzes to test your understanding.
Build a Simple Python Calculator
Show steps
Practice writing Python code by building a simple calculator project.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Design the calculator's functionality and user interface.
- Implement the calculator's basic operations using Python.
- Test and debug the calculator to ensure it works correctly.
Follow Flask Web Development Tutorials
Show steps
Enhance your web development skills by following online tutorials on Flask.
Show steps
Show steps
Show steps
- Find reputable online tutorials on Flask.
- Follow the tutorials thoroughly, completing any code exercises.
- Build a simple Flask web application as a practice project.
Two other activities
Expand to see all activities and additional details
Show all five activities
Participate in Python Code Challenges
Show steps
Sharpen your Python problem-solving abilities by participating in online code challenges.
Browse courses on
Competitive Programming
Show steps
Show steps
Show steps
- Find reputable online code challenge platforms.
- Practice solving problems in various difficulty levels.
- Participate in code challenges and aim to improve your ranking.
Develop an AI-Powered Chatbot
Show steps
Apply your Python and AI skills to create a functional AI-powered chatbot.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Design the chatbot's functionality and user interface.
- Implement the chatbot's core NLP logic.
- Train and test the chatbot to enhance its responses.
- Deploy the chatbot and gather user feedback.
Career center
Learners who complete Developing AI Applications with Python and Flask will develop knowledge and skills
that may be useful to these careers:
Full-Stack Developer
Full-Stack Developer
Full Stack Developers are responsible for the entire software development process, from design to deployment. This course will help you build a strong foundation in Python, a programming language that is used in both front-end and back-end development. You will also learn how to use Flask, a Python-based micro framework for building web applications. This knowledge will be essential for success as a Full Stack Developer.
Software Developer
Software Developer
Software Developers design, develop, and maintain software applications. This course will help you build a strong foundation in Python, a programming language that is widely used in software development. You will also learn how to use Flask, a Python-based micro framework for building web applications. This knowledge will be essential for success as a Software Developer.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will help you build a strong foundation in Python, a programming language that is widely used in software engineering. You will also learn how to use Flask, a Python-based micro framework for building web applications. This knowledge will be essential for success as a Software Engineer.
Web Developer
Web Developer
Web Developers design and develop websites. This course will help you build a strong foundation in Python, a programming language that is widely used in web development. You will also learn how to use Flask, a Python-based micro framework for building web applications. This knowledge will be essential for success as a Web Developer.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. This course will help you build a strong foundation in Python, a programming language that is commonly used in data science. You will also learn how to use Watson AI libraries to build AI-powered applications. This knowledge will be essential for success as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. This course will help you build a strong foundation in Python, a programming language that is widely used in machine learning. You will also learn how to use Watson AI libraries to build AI-powered applications. This knowledge will be essential for success as a Machine Learning Engineer.
Statistical Analyst
Statistical Analyst
Statistical Analysts collect, analyze, and interpret data. This course will help you build a strong foundation in Python, a programming language that is widely used in data analysis. You will also learn how to use Watson AI libraries to build AI-powered applications. This knowledge will be essential for success as a Statistical Analyst.
Research Scientist
Research Scientist
Research Scientists conduct research in a variety of fields, including computer science, engineering, and medicine. This course will help you build a strong foundation in Python, a programming language that is widely used in research. You will also learn how to use Watson AI libraries to build AI-powered applications. This knowledge will be essential for success as a Research Scientist.
AI Engineer
AI Engineer
AI Engineers design and develop AI-powered applications. This course will help you build a strong foundation in Python, a programming language that is widely used in AI development. You will also learn how to use Watson AI libraries to build AI-powered applications. This knowledge will be essential for success as an AI Engineer.
Application Architect
Application Architect
An Application Architect is responsible for designing, developing, and maintaining software applications. This course will help you build a strong understanding of Python, a programming language that is widely used in web development. You will also learn how to use Flask, a Python-based micro framework for building web applications. This knowledge will be essential for success as an Application Architect.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts test and verify the quality of software applications. This course will help you build a strong foundation in Python, a programming language that is widely used in software testing. You will also learn how to write unit tests and perform static code analysis. This knowledge will be essential for success as a Quality Assurance Analyst.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. This course will help you build a strong understanding of the software development process, from design to deployment. You will also learn how to use Python to develop prototypes and test new features. This knowledge will be essential for success as a Product Manager.
Technical Writer
Technical Writer
Technical Writers create documentation for software applications. This course will help you build a strong understanding of the software development process, from design to deployment. You will also learn how to write clear and concise documentation. This knowledge will be essential for success as a Technical Writer.
System Architect
System Architect
System Architects design and develop complex software systems. This course will help you build a strong understanding of the software development process, from design to deployment. You will also learn how to use Python to develop prototypes and test new features. This knowledge will be essential for success as a System Architect.
UX Designer
UX Designer
UX Designers design the user experience for software applications. This course will help you build a strong understanding of the user experience design process. You will also learn how to use Python to develop prototypes and test new features. This knowledge will be essential for success as a UX Designer.
For more career information including salaries, visit:
OpenCourser.com/course/y8ull7/python
Reading list
We've selected nine 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
Developing AI Applications with Python and Flask.
This comprehensive textbook provides a thorough foundation in natural language processing, including topics such as text classification, sentiment analysis, and machine translation. It is valuable for gaining a deeper understanding of the AI techniques used in the course.
This thought-provoking book explores the philosophical and ethical implications of artificial intelligence. It challenges readers to consider the potential benefits and risks of AI while providing a broader perspective on the field.
Save
This comprehensive guide to Python provides numerous examples and recipes for solving common programming problems. It serves as a valuable reference for Python developers at all levels, including those working on AI-based applications.
This practical guide provides a hands-on introduction to machine learning using Python. It covers supervised and unsupervised learning algorithms, model evaluation, and practical applications, which are essential for building AI-powered solutions.
This practical guide covers the essential machine learning libraries in Python, including Scikit-Learn, Keras, and TensorFlow. It provides hands-on examples and exercises for building and evaluating machine learning models, which is crucial for applying AI techniques in practice.
This comprehensive textbook covers a broad range of topics in speech and language processing, including speech recognition, natural language understanding, and dialogue systems. It serves as a valuable reference for gaining a deeper understanding of the foundational concepts and algorithms in AI for speech and language applications.
This practical guide covers the essential concepts and techniques for building web applications using Flask. It is particularly helpful for understanding Flask's architecture and best practices, which are crucial for developing robust and scalable AI applications.
This accessible guide introduces the fundamentals of deep learning using Python. It provides a solid foundation for understanding and working with deep neural networks, which are widely used in AI applications.
Save
This comprehensive textbook provides an in-depth overview of computer vision algorithms and their applications. It covers topics such as image formation, segmentation, recognition, and tracking, which are essential for building AI-powered solutions that analyze and interpret visual data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/y8ull7/python
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Effort
3 weeks of study, 2-3 hours/week
Level
Intermediate
Via
Coursera
Institution
IBM
Instructors
Ramesh Sannareddy
Abhishek Gagneja
Language
English
Transcripts
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Good to know
May fit for learners with a general interest in Python who want to use it for AI development
May fit for learners who need hands-on practice with tasks common in AI development
May fit for learners who would like to get experience with Watson AI libraries
May fit for learners with a basic understanding of Python who are comfortable with writing code
May fit for learners with a basic knowledge of AI concepts
May fit for learners who want to apply their Python skills to build AI solutions
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