Artificial Intelligence using Python - Course by Email
Learn how to use Python to complete Artificial intelligence Projects.
This course is by email. You will get 1 email each day for the next 30 days. The cost of the course is $9.99
You also have the option of buying the Artificial Intelligence using Phython course in the form of an eBOOK.
Please note this is an email only course (or eBook) and there is no option for zoom calls or email exchanges with the instructor. Read the Benefits of learning programming language through daily email lessons
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The following will be covered.
[1] Introduction to AI and machine learning:
Define artificial intelligence and machine learning
Explain the difference between AI and machine learning
Discuss the various applications of AI and machine learning
Introduce Python as a programming language for AI and machine learning
[2] Setting up a Python development environment:
Install Python and necessary libraries and tools
Set up an integrated development environment (IDE)
Familiarization with Python syntax and data types
[3] Exploring and preprocessing data:
Load and explore data sets using Python libraries such as Pandas
Clean and preprocess data using techniques such as missing value imputation and normalization
[4] Building and evaluating machine learning models:
Supervised learning algorithms such as linear regression and support vector machines
Unsupervised learning algorithms such as k-means clustering and principal component analysis
How to evaluate the performance of machine learning models using metrics such as accuracy and mean squared error
[5] Deep learning with neural networks:
Neural networks and deep learning
Build and train neural networks using Python libraries such as TensorFlow and Keras
Techniques for improving the performance of neural networks, such as regularization and model ensembles
[6] Natural language processing:
Introduction to natural language processing (NLP)
Use Python libraries such as NLTK and spaCy to perform tasks such as tokenization, stemming, and part-of-speech tagging
Build and evaluate NLP models for tasks such as language translation and sentiment analysis
[7] Applications of AI and machine learning:
Real-world applications of AI and machine learning in industries such as healthcare, finance, and marketing
This course is by email. You will get 1 email each day for the next 30 days. The cost of the course is $9.99
You also have the option of buying the Artificial Intelligence using Phython course in the form of an eBOOK.
Please note this is an email course (or eBook) and there is no option for zoom calls with the instructor.
To purchase the Email Course, please click here
Below is your Day 1 Course free for you. This will help you to assess if this course will be useful for you or not.
Day 1 Email:
Define artificial intelligence and machine learning
Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. These machines can be trained to perform tasks such as recognizing patterns, learning from data, and making decisions.
Machine learning is a subset of AI that involves the use of algorithms and statistical models to enable computers to learn from data and improve their performance on a specific task without being explicitly programmed. In other words, machine learning algorithms can learn from the data they are given, rather than being explicitly told how to perform a task.
There are several types of machine learning, including:
Supervised learning: This involves training a model on a labeled dataset, where the correct output is provided for each example in the training set. The model makes predictions based on this training data.
Unsupervised learning: This involves training a model on an unlabeled dataset, where the correct output is not provided. The model must discover the underlying structure of the data through techniques such as clustering.
Reinforcement learning: This involves training a model to take actions in an environment in order to maximize a reward. The model learns through trial and error, receiving positive or negative feedback for its actions.
QUIZ
1. What is machine learning?
a. A type of artificial intelligence that allows computers to learn from data without being explicitly programmed
b. A type of artificial intelligence that involves programming computers to perform specific tasks
c. A type of artificial intelligence that involves the use of neural networks to simulate human intelligence
d. A type of artificial intelligence that involves the use of natural language processing techniques
Correct answer: a
2. What is an artificial neural network?
a. A type of machine learning algorithm that is modeled after the structure and function of the human brain
b. A type of machine learning algorithm that is designed to solve problems by making decisions based on rules and heuristics
c. A type of machine learning algorithm that is based on decision trees
d. A type of machine learning algorithm that is based on linear regression
Correct answer: a
3. What is deep learning?
a. A type of machine learning that involves the use of artificial neural networks with many layers
b. A type of machine learning that involves the use of decision trees
c. A type of machine learning that involves the use of linear regression
d. A type of machine learning that involves the use of natural language processing techniques
Correct answer: a
4. What is the goal of supervised learning?
a. To learn the relationship between input data and output data
b. To learn how to classify data into different categories
c. To learn how to make predictions based on input data
d. All of the above
Correct answer: d
5. What is the goal of unsupervised learning?
a. To learn the relationship between input data and output data
b. To learn how to classify data into different categories
c. To learn how to make predictions based on input data
d. To find hidden patterns in data
Correct answer: d
Explain the difference between AI and machine learning
Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. These machines can be trained to perform tasks such as recognizing patterns, learning from data, and making decisions.
Machine learning, on the other hand, is a subset of AI that involves the use of algorithms and statistical models to enable computers to learn from data and improve their performance on a specific task without being explicitly programmed. In other words, machine learning algorithms can learn from the data they are given, rather than being explicitly told how to perform a task.
One key difference between AI and machine learning is that AI is a broader concept that includes machine learning, as well as other techniques for enabling computers to perform tasks that typically require human intelligence. Machine learning, on the other hand, is focused specifically on the use of algorithms and statistical models to enable computers to learn from data.
Another difference is that AI can be divided into two categories: narrow or general. Narrow AI is designed to perform a specific task, while general AI is capable of performing a wide range of tasks. Machine learning is typically used to create narrow AI, while general AI is still an area of active research.
QUIZ
1. What is the main difference between artificial intelligence (AI) and machine learning?
a. AI involves the use of natural language processing techniques, while machine learning does not
b. AI involves programming computers to perform specific tasks, while machine learning involves training computers to learn from data
c. Machine learning is a type of AI, while AI is a broader term that includes machine learning
d. There is no difference between AI and machine learning
Correct answer: c
2. What is an example of a task that might be performed by AI, but not by machine learning?
a. Image classification
b. Speech recognition
c. Predictive maintenance
d. Sentiment analysis
Correct answer: a
3. What is an example of a task that might be performed by machine learning, but not by AI?
a. Image classification
b. Speech recognition
c. Predictive maintenance
d. Sentiment analysis
Correct answer: c
4. Which of the following is NOT a characteristic of AI?
a. Ability to learn from data
b. Ability to make decisions
c. Ability to process natural language
d. Ability to perform tasks that would be difficult or impossible for humans
Correct answer: a
5. Which of the following is NOT a characteristic of machine learning?
a. Ability to learn from data
b. Ability to make decisions
c. Ability to process natural language
d. Ability to perform tasks that would be difficult or impossible for humans
Correct answer: d
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