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Numerical Methods for Engineers
by Jeffrey R. Chasnov- 4.9
Approx. 40 hours to complete
We learn how to use MATLAB to solve numerical problems. Access to MATLAB online and the MATLAB grader is given to all students who enroll. Students should have already studied a programming language, and be willing to learn MATLAB. How to Write Math in the Discussions Using MathJax How to Solve Three Nonlinear equations...
Six Sigma Tools for Improve and Control
by Christina Scherrer, PhD , David Cook, PhD , Gregory Wiles, PhD , Bill Bailey, PhD- 4.8
Approx. 9 hours to complete
This course will provide you will the tools necessary to complete the final components of the analyze phase as well as the improve and control phases of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. How To Do A Hypothesis Test How to do a Hypothesis Test - Recommended Reading...
Managing Talent
by Scott DeRue, Ph.D. , Maxim Sytch, Ph.D. , Cheri Alexander- 4.6
Approx. 12 hours to complete
In this course, you will learn best practices for selecting, recruiting, and onboarding talent. You will also learn about the key approaches to measuring performance and evaluating your employees. In addition, you will learn how to develop and coach your talent so that they can realize their full potential at work....
Pointers, Arrays, and Recursion
by Andrew D. Hilton , Anne Bracy , Genevieve M. Lipp- 4.4
Approx. 21 hours to complete
The third course in the specialization Introduction to Programming in C introduces the programming constructs pointers, arrays, and recursion. Pointers provide control and flexibility when programming in C by giving you a way to refer to the location of other data. Pointers to Structs Pointers to Pointers Pointers to Sophisticated Types...
Influence
by Cade Massey- 4.7
Approx. 9 hours to complete
What does it mean to be influential? How does one persuade others to pursue a unified goal? How does one leverage power? In this course, you’ll learn how to develop influence and to become more effective in achieving your organizational goals. Introduction to Coalitions Introduction to Persuasion...
Setting Expectations & Assessing Performance Issues
by Kris Plachy- 4.7
Approx. 18 hours to complete
That’s exactly what you’ll learn to do in this course! You will explore how to collaboratively develop expectations with those you lead. When you encounter expectations that are not being met, you’ll learn how to use "Coaching Algebra" to determine the underlying issues that are impeding performance, and how to respond as a manger-coach....
Basic Recommender Systems
by Paolo Cremonesi- 3.9
Approx. 12 hours to complete
You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of different recommender system alternatives. You'll learn as well how to design recommender systems tailored for new application domains, also considering surrounding social and ethical issues such as identity, privacy, and manipulation. Introduction to Recommender Systems...
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Mastering Web3 with Waves
by Inal Kardanov , Aleksei Pupyshev- 0.0
Approx. 18 hours to complete
We are on the threshold of transitioning to the next generation of the internet, Web 3. Each of the six weekly modules includes video tutorials, quizzes of 14 to 18 questions, and practical assignments. Sign up for the course and learn vital Web 3. How to: simple Node. How to: simple interactive React....
IT Security: Defense against the digital dark arts
by Google Career CertificatesTop Instructor- 4.8
Approx. 30 hours to complete
We’ll give you some background of encryption algorithms and how they’re used to safeguard data. ● how to evaluate potential risks and recommend ways to reduce risk. ● how to help others to grasp security concepts and protect themselves. How to Add Google IT Support Certificate to Your Resume and LinkedIn Profile...
Machine Learning for Accounting with Python
by Linden Lu- 0.0
Approx. 63 hours to complete
MODULE 1: INTRODUCTION TO MACHINE LEARNING 1 Introduction to Machine Learning 2 Introduction to Data Preprocessing 3 Introduction to Machine Learning Algorithms 1 Introduction to Linear Regression How to apply machine learning models on datasets with Python in Jupyter Notebook. How to evaluate machine learning models. How to optimize machine learning models....