English
Log In
Machine Learning in Python With Big Data (Level 4)
Class Experience
In this course, students will gain a foundational understanding of machine learning concepts and techniques through hands-on projects using AICode101 and Google Colaboratory. They will learn to set up accounts, use machine learning tools, and apply concepts to real-world data, culminating in the creation and presentation of their final projects. For a week to week program, check out the syllabus.
10 lessons//10 Weeks
Week 1Lesson 1OverviewDesigned to provide students with a very basic understanding of machine learning concepts that they will be able to apply in the course. They will also be shown the tools they will be using throughout the course. Task: Set up AICode101 Accounts Students will be tasked with creating AICode101 accounts and walking through the website to learn how it will be used in the course.Week 2Lesson 2Image Recognition Project with AICode101Designed to provide students with an introduction to image recognition in machine learning. Students will be able to apply concepts in machine learning to generate their own program to recognize categorized images. Task: Image Recognition Project Students will be tasked with creating an AICode101 image recognition project. Through this, they will learn key fundamentals of image recognition in machine learning.Week 3Lesson 3‘Rain in Australia’ Number Project with AICode101Designed to provide students with an introduction to classification with data in machine learning. Students will be able to apply concepts in machine learning to generate their own program to predict weather. Task: Number Project Students will be tasked with creating an AICode101 number project. Through this, they will learn key fundamentals of classification in machine learning.Week 4Lesson 4The Stock Market FundamentalsDesigned to provide students with an introduction to the stock market in preparation for the next lesson. Students will learn about what the stock market is and how it can be incorporated into machine learning. Task: Stock Market Search Students will be tasked with navigating financial sites to view different stocks and the associated data that defines a stock and its performance.Week 5Lesson 5Stock Price Prediction with AICode101Designed to provide students with an introduction to data manipulation for use in machine learning and functional data classification through the use of models. Task: Data Analysis and Cleanup Students will be given data to analyze for important features and “clean up” the data to ensure no issues in calculation or model generation. Task: Model Generation Students will generate models using the data they have handled to make predictions.Week 6Lesson 6Flower Classification Project with Google ColaboratoryDesigned to provide students with an introduction to machine learning in the Python programming language. Students will learn how to read data, generate models, and make predictions using the language and the “Google Colaboratory” program. Task: Data Analysis and Cleanup Students will be given data to load into their “notebooks” that can then be cleaned up, graphed, and analyzed. Task: Model Generation and Analysis Students will generate models to classify species of flowers as a basic exampWeek 7Lesson 7Stock Market Price Prediction with Google ColaboratoryDesigned to provide students with a more advanced understanding of machine learning fundamentals learned throughout the course. They will be able to apply the fundamentals to gain a deeper understanding of machine learning and its applications. Task: Data Analysis and Cleanup Students will be given data to load into their “notebooks” that can then be cleaned up, graphed, and analyzed. Task: Model Generation and AnalysisWeek 8Lesson 8NBA Draft Pick Prediction with Google ColaboratoryDesigned to provide students with a more advanced understanding of machine learning fundamentals learned throughout the course. They will be able to apply the fundamentals to gain a deeper understanding of machine learning and its applications. Task: Data Analysis and Cleanup Students will be given data to load into their “notebooks” that can then be cleaned up, graphed, and analyzed.Week 9Lesson 9Class Review with KahootStudents will review all of the material learned in the course in a fun review class. The Kahoot quiz software will be used to provide a fun, interactive experience for students.Week 10Lesson 10Final Project PresentationsStudents will present their final projects based off of data provided to them in a previous class. They will have time to work on their projects at the beginning of class.
- Students will gain a foundational understanding of machine learning concepts and techniques through hands-on projects using AICode101 and Google Colaboratory.
- They will learn to set up accounts, use machine learning tools, and apply concepts to real-world data, culminating in the creation and presentation of their final projects.
1 - 2 hours per week outside of class
Homework
Frequency: 1-2 throughout the classFeedback: includedDetails: Projects are not mandatory but we strongly encourage students to complete them.Assessment
Frequency: includedDetails:
Reviews
Group Class
$269
for 10 classes1x per week, 10 weeks
60 min
Completed by 114 learners
Live video meetings
Ages: 13-18
4-10 learners per class
Financial Assistance
Tutoring
More to Explore
Iew FablesTerrible ToysAnxiety DisorderIntro To Writing Fascinating BRevolutionMulti-digit MultiplicationHow To Make Awesome Animated Movies Intro To AnimationStruggling MathAbout MeKorean WarBecome An IllustratorDietitianBeginning Piano Adventures Group Piano Lessons For BeginnersRainbow RoomPlay Flute