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种子名称：
[Tutorialsplanet.NET] Udemy - The Product Management for AI & Data Science Course 2023
文件类型：
视频
文件数目：
67个文件
文件大小：
1.37 GB
收录时间：
2024-7-10 20:14
已经下载：
3次
资源热度：
73
最近下载：
2024-8-17 02:49
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种子包含的文件
[Tutorialsplanet.NET] Udemy - The Product Management for AI & Data Science Course 2023.torrent
01 - Intro to Product Management for AI & Data/001 Introduction.mp490.26MB
01 - Intro to Product Management for AI & Data/002 Course Overview.mp463.94MB
01 - Intro to Product Management for AI & Data/003 Growing Importance of an AI & Data PM.mp467.95MB
01 - Intro to Product Management for AI & Data/004 The Role of a Product Manager.mp414.46MB
01 - Intro to Product Management for AI & Data/005 Differentiation of a PM in AI & Data.mp476.25MB
01 - Intro to Product Management for AI & Data/006 Product Management vs. Project Management.mp412.09MB
02 - Key Technological Concepts for AI & Data/001 A Product Manager as an Analytics Translator.mp411.38MB
02 - Key Technological Concepts for AI & Data/002 Data Analysis vs. Data Science.mp48.94MB
02 - Key Technological Concepts for AI & Data/003 A Traditional Algorithm vs. AI.mp4129.37MB
02 - Key Technological Concepts for AI & Data/004 Explaining Machine Learning.mp4134.19MB
02 - Key Technological Concepts for AI & Data/005 Explaining Deep Learning.mp415.79MB
02 - Key Technological Concepts for AI & Data/006 When to use Machine Learning vs. Deep Learning.mp417.98MB
02 - Key Technological Concepts for AI & Data/007 Supervised, Unsupervised, & Reinforcement Learning.mp414.86MB
03 - Business Strategy for AI & Data/001 AI Business Model Innovations.mp414.32MB
03 - Business Strategy for AI & Data/002 When to Use AI.mp411.71MB
03 - Business Strategy for AI & Data/003 SWOT Analysis.mp410.54MB
03 - Business Strategy for AI & Data/004 Building a Hypothesis.mp412.48MB
03 - Business Strategy for AI & Data/005 Testing a Hypothesis.mp411.28MB
03 - Business Strategy for AI & Data/006 AI Business Canvas.mp418.09MB
04 - User Experience for AI & Data/001 User Experience for Data & AI.mp411.91MB
04 - User Experience for AI & Data/002 Getting to the Core Problem.mp419.15MB
04 - User Experience for AI & Data/003 User Research Methods.mp419.62MB
04 - User Experience for AI & Data/004 Developing User Personas.mp412.91MB
04 - User Experience for AI & Data/005 Prototyping with AI.mp413.19MB
05 - Data Management for AI & Data/001 Data Growth Strategy.mp424.75MB
05 - Data Management for AI & Data/002 Open Data.mp48.74MB
05 - Data Management for AI & Data/003 Company Data.mp49.55MB
05 - Data Management for AI & Data/004 Crowdsourcing Labeled Data.mp420.24MB
05 - Data Management for AI & Data/005 New Feature Data.mp412.72MB
05 - Data Management for AI & Data/006 AcquisitionPurchase Data Collection.mp410.36MB
05 - Data Management for AI & Data/007 Databases, Data Warehouses, & Data Lakes.mp411.63MB
06 - Product Development for AI & Data/001 AI Flywheel Effect.mp414.71MB
06 - Product Development for AI & Data/002 Top & Bottom Problem Solving.mp49.76MB
06 - Product Development for AI & Data/003 Product Ideation Techniques.mp419.61MB
06 - Product Development for AI & Data/004 Complexity vs. Benefit Prioritization.mp417.31MB
06 - Product Development for AI & Data/005 MVPs & MVDs (Minimum Viable Data).mp425.35MB
06 - Product Development for AI & Data/006 Agile & Data Kanban.mp414.64MB
07 - Building The Model/001 Who Should Buid Your Model.mp414.96MB
07 - Building The Model/002 Enterpise AI.mp413.27MB
07 - Building The Model/003 Machine Learning as a Service (MLaaS).mp413.57MB
07 - Building The Model/004 In-House AI & The Machine Learning Lifecycle.mp410.2MB
07 - Building The Model/005 Timelines & Diminishing Returns.mp414MB
07 - Building The Model/006 Setting a Model Performance Metric.mp414.05MB
08 - Evaluating Performance/001 Dividing Test Data.mp411.96MB
08 - Evaluating Performance/002 The Confusion Matrix.mp414.24MB
08 - Evaluating Performance/003 Precision, Recall & F1 Score.mp417.04MB
08 - Evaluating Performance/004 Optimizing for Experience.mp418.09MB
08 - Evaluating Performance/005 Error Recovery.mp410.37MB
09 - Deployment & Continuous Improvement/001 Model Deployment Methods.mp415.72MB
09 - Deployment & Continuous Improvement/002 Monitoring Models.mp412.53MB
09 - Deployment & Continuous Improvement/003 Selecting a Feedback Metric.mp410.86MB
09 - Deployment & Continuous Improvement/004 User Feedback Loops.mp410.46MB
09 - Deployment & Continuous Improvement/005 Shadow Deployments.mp49.02MB
10 - Managing Data Science & AI Teams/001 AI Hierarchy of Needs.mp413.42MB
10 - Managing Data Science & AI Teams/002 AI Within an Organization.mp412.38MB
10 - Managing Data Science & AI Teams/003 Roles in AI & Data Teams.mp413.78MB
10 - Managing Data Science & AI Teams/004 Managing Team Workflow.mp49.42MB
10 - Managing Data Science & AI Teams/005 Dual & Triple-Track Agile.mp411.96MB
11 - Communication/001 Internal Stakeholder Management.mp414.49MB
11 - Communication/002 Setting Data Expectations.mp413.79MB
11 - Communication/003 Active Listening & Communication.mp412.56MB
11 - Communication/004 Compelling Presentations with Storytelling.mp412.44MB
11 - Communication/005 Running Effective Meetings.mp413.78MB
12 - Ethics, Privacy, & Bias/001 AI User Concerns.mp410.39MB
12 - Ethics, Privacy, & Bias/002 Bad Actors & Security.mp414.51MB
12 - Ethics, Privacy, & Bias/003 AI Amplifying Human Bias.mp416.57MB
12 - Ethics, Privacy, & Bias/004 Data Laws & Regulations.mp410.79MB
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