Friday, 29 December 2023

AI Product Management Specialization

 


What you'll learn

Identify when and how machine learning can applied to solve problems

Apply human-centered design practices to design AI product experiences that protect privacy and meet ethical standards

Lead machine learning projects using the data science process and best practices from industry

Join Free:AI Product Management Specialization

Specialization - 3 course series

Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems.  This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects.

This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems.  Learners will build skills in applying the data science process and industry best practices to lead machine learning projects, and develop competency in designing human-centered AI products which ensure privacy and ethical standards. The courses in this Specialization focus on the intuition behind these technologies, with no programming required, and merge theory with practical information including best practices from industry.  Professionals and aspiring professionals from a diverse range of industries and functions, including product managers and product owners, engineering team leaders, executives, analysts and others will find this program valuable.   

Applied Learning Project

Learners will implement three projects throughout the course of this Specialization:

1) In Course 1, you will complete a hands-on project where you will create a machine learning model to solve a simple problem (no coding necessary) and assess your model's performance.

2) In Course 2, you will identify and frame a problem of interest, design a machine learning system which can help solve it, and begin the development of a project plan.

3) In Course 3, you will perform a basic user experience design exercise for your ML-based solution and analyze the relevant ethical and privacy considerations of the project.

0 Comments:

Post a Comment

Popular Posts

Categories

100 Python Programs for Beginner (51) AI (34) Android (24) AngularJS (1) Assembly Language (2) aws (17) Azure (7) BI (10) book (4) Books (173) C (77) C# (12) C++ (82) Course (67) Coursera (226) Cybersecurity (24) data management (11) Data Science (128) Data Strucures (8) Deep Learning (20) Django (14) Downloads (3) edx (2) Engineering (14) Excel (13) Factorial (1) Finance (6) flask (3) flutter (1) FPL (17) Google (34) Hadoop (3) HTML&CSS (47) IBM (25) IoT (1) IS (25) Java (93) Leet Code (4) Machine Learning (59) Meta (22) MICHIGAN (5) microsoft (4) Nvidia (3) Pandas (4) PHP (20) Projects (29) Python (930) Python Coding Challenge (358) Python Quiz (22) Python Tips (2) Questions (2) R (70) React (6) Scripting (1) security (3) Selenium Webdriver (3) Software (17) SQL (42) UX Research (1) web application (8) Web development (2) web scraping (2)

Followers

Person climbing a staircase. Learn Data Science from Scratch: online program with 21 courses