Bias

Sort options

Analyze Datasets and Train ML Models using AutoML (Coursera)

Oct 25th 2021
Analyze Datasets and Train ML Models using AutoML (Coursera)
Course Auditing
Categories
Effort
Languages
In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms. With Amazon SageMaker Clarify and Amazon SageMaker Data Wrangler, you will analyze a dataset for statistical bias, transform the dataset into [...]
0
No votes yet
Oct 25th 2021
Course Auditing
41.00 EUR/month

Prepare Data for Exploration (Coursera)

Oct 25th 2021
Prepare Data for Exploration (Coursera)
Course Auditing
Categories
Effort
Languages
This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new [...]
0
No votes yet

Leading Diverse Teams (Coursera)

This course addresses the leadership skills and competencies that are requisite for leading across cultures in a global business environment. Participants will learn from frameworks, principles, and practices regarding how to leverage their cross-cultural business experiences for greater influence and effectiveness across cultural contexts (teams, organizations, regions, countries, etc.). [...]
0
No votes yet

Inclusive Leadership: The Power of Workplace Diversity (Coursera)

This course will equip and empower you to be a highly inclusive leader. You will learn principles, perspectives and practices that help to reap the power of workplace diversity. Workplace diversity has expanded beyond traditional demographics such as gender, race, and ethnicity. Those categories always will matter. [...]
0
No votes yet

Promote the Ethical Use of Data-Driven Technologies (Coursera)

tudents will learn what emerging technologies are and how they can be used to create data driven solutions. You will learn types of bias and common ethical theories and how they can be applied to emerging technology, and examine legal and ethical privacy concepts as they relate to technologies [...]
0
No votes yet

Artificial Intelligence Data Fairness and Bias (Coursera)

Oct 25th 2021
Artificial Intelligence Data Fairness and Bias (Coursera)
Course Auditing
Categories
Effort
Languages
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects [...]
0
No votes yet
Oct 25th 2021
Course Auditing
41.00 EUR/month

Artificial Intelligence Ethics in Action (Coursera)

Oct 25th 2021
Artificial Intelligence Ethics in Action (Coursera)
Course Auditing
Categories
Effort
Languages
AI Ethics research is an emerging field, and to prove our skills, we need to demonstrate our critical thinking and analytical ability.
0
No votes yet

Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls (Coursera)

Machine learning. Your team needs it, your boss demands it, and your career loves it. After all, LinkedIn places it as one of the top few "Skills Companies Need Most" and as the very top emerging job in the U.S. This course will show you how machine learning works. [...]
0
No votes yet

Biases and Portfolio Selection (Coursera)

Investors tend to be their own worst enemies. In this third course, you will learn how to capitalize on understanding behavioral biases and irrational behavior in financial markets. You will start by learning about the various behavioral biases – mistakes that investors make and understand their reasons. You [...]
1
Average: 1 ( 4 votes )

Data Science in Real Life (Coursera)

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The [...]
8
Average: 8 ( 3 votes )