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Supervised Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
Approx. 11 hours to complete
You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. -Use a variety of error metrics to compare and select the classification model that best suits your data Optional: How to create a project in IBM Watson Studio...
Supervised Machine Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
Approx. 11 hours to complete
You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. -Use a variety of error metrics to compare and select the classification model that best suits your data Optional: How to create a project in IBM Watson Studio...
AWS Cloud Practitioner Essentials
by Rudy Chetty , Morgan Willis , Blaine SundrudTop Instructor- 4.8
Approx. 20 hours to complete
If you’re new to the cloud, whether you’re in a technical or non-technical role such as finance, legal, sales, marketing, this course will provide you with an understanding of fundamental AWS Cloud concepts to help you gain confidence to contribute to your organization’s cloud initiatives. How to Provision AWS Resources (Part 1)...
Spanish Vocabulary: Sports, Travel, and the Home
by Dr. Robert Blake- 4.7
Approx. 16 hours to complete
Building on the vocabulary and skills that you have already mastered, this third course of the specialization will introduce new vocabulary that will prepare you to discuss sports, pastimes and politics -- important cultural elements of the Spanish-speaking world. You’ll also add new vocabulary relating to travel and living arrangements. How to be Successful in this Course...
Architecting with Google Kubernetes Engine: Production
by Google Cloud Training- 4.7
Approx. 12 hours to complete
How to Send Feedback Understand how logging is implemented and Kubernetes, and how GKE extends that basic functionality using Google Cloud's operations suite...
Identifying Security Vulnerabilities
by Sandra Escandor-O'Keefe- 4.6
Approx. 13 hours to complete
We will learn about the concepts of threat modeling and cryptography and you'll be able to start to create threat models, and think critically about the threat models created by other people. We'll cover how to effectively store password-related information, and not to store the actual plaintext passwords. Cryptography Basics: Application to Threat Models...
Business English: Marketing and Sales
by Andrea Mürau HarawayTop Instructor , Wanda Huber , Jenny Young , Beatriz Fuentes-Anderson- 4.7
Approx. 32 hours to complete
If you work in marketing, sales, or advertising, you already know that effective communication is a requirement. 13 Nuts & Bolts ~ What is a Tagline? 13 How to Get People to Do Stuff: Nouns or Verbs? 22 A Quick Guide to Writing Your Elevator Pitch: With Examples! 26 Steps to Preparing a Good Elevator Pitch...
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Economic Growth and Distributive Justice Part II - Maximize Social Wellbeing
by Professor Yoram Y. Margalioth- 4.6
Approx. 7 hours to complete
• Climate change: the atmosphere and oceans as public goods, and how smart (Pigovian) taxation can be used to combat the rapidly increasing threats to our planet; • design a tax and transfer system to maximize the happiness of individuals 6 Discussing Thomas Piketty’s Book “Capital in the 21st Century”: Taxation of Capital; High Inequality as a Threat to Democracy...
Python and Jupyter Notebooks for beginners
by Bluelime Learning Solutions- 3.7
2.5 hours on-demand video
Python is a very popular and powerful programming language. Python is versatile and can be fun to use in creating powerful and useful applications. Python can be used to create a variety of applications types How to install Jupyter Notebook How to run the Jupyter Notebook Server Notebook Dashboard Create Notebooks...
$11.99
Wrangling Data in the Tidyverse
by Carrie Wright, PhD , Shannon Ellis, PhD , Stephanie Hicks, PhD , Roger D. Peng, PhD- 4.8
Approx. 14 hours to complete
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. Converting Numeric Levels to factors: ifelse() + factor() Apply Tidyverse functions to transform non-tidy data to tidy data...