Python AI Development: Practice
Python
| Intermediate
- 14 videos | 1h 20m 27s
- Includes Assessment
- Earns a Badge
In this course, you'll learn about development of AI with Python, starting with simple projects and ending with comprehensive systems. You'll examine various Python environments and ways to set them up and begin coding, leaving you with everything you need to begin building your own AI solutions in Python.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Configure the python environment for developing ai
Specify the role of anaconda in keeping clear working environments
Specify the advantages of jupyter notebooks and create jupyter notebook files connected to appropriate kernel environment
Specify the advantages of the google colab environment and create files in the environment
Use large datasets for exploring data and statistics
Apply pre-processing techniques commonly used in ai development -
Describe the steps needed to create machine learning models and identify guidelines for using them
Describe the steps needed to create deep learning models and identify guidelines for using them
Work with a hand written digits dataset and implement a simple classification model in python
Work with a housing prices dataset and implement a simple regression model in python
Create a pilot distraction predictor by applying deep learning techniques
Configure a distracted driver detection device in python using the pilot distraction predictor
Summarize the key concepts covered in this course
IN THIS COURSE
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2m 4s
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2m 37sDuring this video, you will learn how to configure the Python environment for developing AI. FREE ACCESS
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3. Understanding Anaconda Distribution4m 2sAfter completing this video, you will be able to specify the role of Anaconda in maintaining clear working environments. FREE ACCESS
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4. Jupyter Notebooks3m 10sAfter completing this video, you will be able to specify the advantages of Jupyter Notebooks and create Jupyter Notebook files connected to an appropriate kernel environment. FREE ACCESS
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5. Google Colab2m 39sAfter completing this video, you will be able to specify the advantages of the Google Colab environment and create files in the environment. FREE ACCESS
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6. Data Exploration9m 7sLearn how to use large datasets to explore data and statistics. FREE ACCESS
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7. Data Pre-processing14m 3sLearn how to apply pre-processing techniques commonly used in AI development. FREE ACCESS
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8. Basic ML Models4m 9sAfter completing this video, you will be able to describe the steps needed to create machine learning models and identify guidelines for their use. FREE ACCESS
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9. Basic DL Models3m 46sUpon completion of this video, you will be able to describe the steps needed to create deep learning models and identify guidelines for using them. FREE ACCESS
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10. Classifying Hand Written Digits10m 37sFind out how to work with a handwritten digits dataset and implement a simple classification model in Python. FREE ACCESS
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11. Predicting House Prices8m 28sIn this video, you will learn how to work with a housing prices dataset and implement a simple regression model in Python. FREE ACCESS
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12. Pilot Distraction Prediction7m 15sLearn how to create a pilot distraction predictor by applying deep learning techniques. FREE ACCESS
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13. Distracted Driver Detection7m 4sDuring this video, you will learn how to configure a distracted driver detection device in Python using the pilot distraction predictor. FREE ACCESS
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14. Course Summary1m 26sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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