This Course Includes
- 4 hours videos
- 40+ lessons
- Learning material and Resources
- Full time life access
- Certificate of completion
- Access on mobile
What you will Learn
- Student will get an introduction to Python.
- Student will learn basic concepts of Python like Data types, decision making, loops and classes
- Student will practice different libraries like Numpy and Matplotlib
- Overview of Machine learning and AI and their benefits
- Students will learn and implement different models of machine learning
- Student will be able to create AI model using IBM Watson
Requirements
- There are no pre requisite however student having a laptop or PC would help in practicing hands on and to learn by doing.
Course Description
Automation Play brings you an interactive and practical online course on Artificial Intelligence and Machine learning with Python with in-depth content and hands-on experience.
The course has been designed for absolute beginners to learn Machine Learning and Artificial Intelligence from scratch.
In this course, we will be covering in-depth knowledge of different models like line regression, decision tree, random forest, SVR, etc. Moreover, Student will also learn about creating AI model using IBM Watson. We have also covered basic concepts of Python and some essential libraries like Numpy, Matplotlib, and Pandas as pre-requisite.
Course Content
- Course Overview
- Introduction to Machine Learning & AI
- Benefits of AI
- Applications of AI
- Artificial Intelligence and IoT
- Introduction to Jupyter Notebook
- Installation of Colab
- Introduction to Python
- Data types in Python
- Conditional statements, Loops , Functions and Classes
- Numpy & Matplotlib
- Models of Machine learning and their applications - Regressors
- Models of Machine learning and their applications - Classifiers
- Implementation of Models- Regressors
- Implementation of Models-Classifiers
- Creating AI model with IBM Watson
Deliverable
- Training Lectures
- Learning resources
- Lifetime Access to the course
Who this course is for:
- Engineering Students
- Tech enthusiasts
- Industrial Professionals
- Technicians
- Automation Hobbyists
Software
- Jupyter Notebook
Example Curriculum
Introduction To Artificial Intelligence & Machine Learning
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after you enroll
Introduction to Python
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after you enroll
- Jupyter Notebook (1:56)
- Installation of Colab (4:59)
- Introduction to Python (4:20)
- Data types in Python (10:32)
- Lists in Python (10:11)
- Tuples in Python (5:22)
- Sets in Python (8:41)
- Dictionary in Python (5:51)
- Conditional Statements in Python (8:31)
- Conditional Statement in Python-Part#2 (8:42)
- Loops in Python: While Loop (6:24)
- Loops in Python: For Loop (7:41)
- Functions in Python (6:16)
- Classes in Python (7:27)
Numpy in Python
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after you enroll
Matplotlib In Python
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after you enroll
Models OF Machine Learning
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after you enroll
- Simple Linear Regression (3:36)
- Multiple Linear Regression (3:48)
- Polynomial Regressison (3:59)
- Support Vector Regressor (2:29)
- Decision Tree Regressor (2:24)
- Random Forest Regressor (3:18)
- Random Forest Classifier (3:43)
- KNN Classifier (3:29)
- Support Vector Machine (3:36)
- Naive Bayes Classifier (3:53)
- Decision Tree Classifier (3:37)
Implementation of Models
Available in
days
days
after you enroll
Creating AI Model with IBM Watson
Available in
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after you enroll
Team Automation Play
Team work makes the dream work! Team Automation Play consists of engineers from well reputed universities and organizations who are all willing to work towards a common goal of empowering students and professionals in their respective fields.