.pro-gallery-wix-wrapper {display: block !important;} .pro-gallery-wix-wrapper .gallery-item-container {opacity: 1 !important; display: block !important;}

Intro to: Prompt Engineering for Machine Learning

Name: Intro to: Prompt Engineering for Machine Learning
SKU: it_pestmldj_04_enus

SKU it_pestmldj_04_enus

Machine learning involves creating models that dynamically change based on the data from which they are created.

Within machine learning, three fundamental problems—regression, classification, and clustering—are the focus of a variety of solution techniques.

Course Details:

You'll begin this course by conducting regression analysis. You'll analyze and visualize data to get a sense of variables with predictive power, split data into training & test sets, and create & train models.

You'll also explore the impact of training a model on imbalanced data, and with generative artificial intelligence (AI) assistance, see how you can mitigate this by leveraging oversampling and under-sampling techniques. Perform clustering and evaluate it using the silhouette and Davies-Bouldin scores.

At course completion, you will have a good understanding of key concepts of machine learning and how to perform regression analysis, classification of data, and clustering.

This course contains 13 modules (Total Duration: 1hr, 43mins)

Course Overview
Regression, Classification, and Clustering
Using Regression Analysis
Interpreting Relationships in Data with GPT-4
Training a Regression Model with Google Bard's Help
Analyzing Data for Classification
Preprocessing Data & Training Models
Evaluating Classification Models with Prompt Engineering
Training a Classification Model with an Imbalanced Dataset
Oversampling & Undersampling Data with Bard's Help
Training a Clustering Model with Prompt Engineering
Evaluating Clustering Models with Generative AI Help
Course Summary

Digital Product Notice:

This is a Digital Product!
After course purchase, you'll receive your credentials via email to access the online Student Portal to view your course material.

Refund/Exchange Policy:

Our online courses are digital products that will be delivered via online access through our Student Portal.

Digital products are ineligible for refunds or exchanges.

Course ID Code:

ID: [it_pestmldj_04_enus]
*to be used for course registration*

Recommended Experience:

Beginner Level

This course is suitable for everyone, including students, professionals, and enthusiasts.

Flexible Schedule

Learn at your own pace!

Certificate of Completion

Earn a Professional Career Certification from the State University of New York.

Course
Overviews & Objectives

Install Anaconda Python on Windows & MacOS
Execute commands on the Python shell.
Perform basic math operations.
Execute arithmetic operations on variables.
Work with built-in functions.
Create & use complex data types (lists, tuples, sets, etc.)
Perform type conversions.
Create strings with various quotes.
How to perform basic math and logical operations in Python.
Create Python variables and see how you can assign and access values stored in these variables.
Use built-in functions in the core Python programming language to perform simple calculations and operations.
Explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case.
Examine the use of complex data types, such as lists, tuples, sets, and dictionaries.
When you're finished with this course, you'll be able to execute simple Python commands on Jupyter notebooks.

Overview:

In Module #1, you'll learn the basics of Python and its philosophy, setting up Python, and writing a basic program with built-in data types, loops, and conditionals.

Objectives:

Setting Up
A Basic Program
Data Types
Sequence Types
Collection & Mapping Types in Python
Loops & Conditionals
Practice: Writing a Python Program

Overview:

Python is a lot more than a scripting language, and can be used to create OOP applications using classes, or using a functional paradigm.

This module covers some of the ways Python programs can execute. You'll learn about building your own custom functions and classes, and documentation and file handling.

Objectives:

Modules & Functions
Classes
Documenting Code
Files
Practice: Creating Classes

Course
Overviews & Objectives

Install Anaconda Python on Windows & MacOS
Execute commands on the Python shell.
Perform basic math operations.
Execute arithmetic operations on variables.
Work with built-in functions.
Create & use complex data types (lists, tuples, sets, etc.)
Perform type conversions.
Create strings with various quotes.
How to perform basic math and logical operations in Python.
Create Python variables and see how you can assign and access values stored in these variables.
Use built-in functions in the core Python programming language to perform simple calculations and operations.
Explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case.
Examine the use of complex data types, such as lists, tuples, sets, and dictionaries.
When you're finished with this course, you'll be able to execute simple Python commands on Jupyter notebooks.

Overview:

In Module #1, you'll learn the basics of Python and its philosophy, setting up Python, and writing a basic program with built-in data types, loops, and conditionals.

Objectives:

Setting Up
A Basic Program
Data Types
Sequence Types
Collection & Mapping Types in Python
Loops & Conditionals
Practice: Writing a Python Program

Overview:

Python is a lot more than a scripting language, and can be used to create OOP applications using classes, or using a functional paradigm.

This module covers some of the ways Python programs can execute. You'll learn about building your own custom functions and classes, and documentation and file handling.

Objectives:

Modules & Functions
Classes
Documenting Code
Files
Practice: Creating Classes

Frequently Asked Questions

You will receive a username & password to access the Student Portal and view your course material.

Please allow 24-48 hours for your student registration and credentials to be assigned.
Upon course completion, you will be mailed a Professional Career Certification from the State University of New York.

Intro to: Prompt Engineering for Machine Learning

Course Details:

Digital Product Notice:

Refund/Exchange Policy: