Cryptography with Dan Boneh

[no audit](no audit) ans1 ans2
sdf

[can't audit?](cannot audit?)
Penetration Testing

Incident Response

Digital Forensics

Introduction to Scripting

Game Theory I

Game Theory II: Advanced Applications

aud
- voting schemes: Condorcet vs Borda Count
- c
GTOC-II-Syllabus
Social Choice

Mechanism Design

Efficient Mechanisms

Auctions

Machine Learning Engineering for Production (MLOps) Specialization

aud ans
Lesson 1

Week 1: Overview of the ML Lifecycle and Deployment Week 2: Selecting and Training a Model Week 3: Data Definition and Baseline

Lesson 2

Week 1: Collecting, Labeling, and Validating data Week 2: Feature Engineering, Transformation, and Selection Week 3: Data Journey and Data Storage Week 4: Advanced Data Labeling Methods, Data Augmentation, and Preprocessing Different Data Types

Lesson 3

Week 1: Neural Architecture Search Week 2: Model Resource Management Techniques Week 3: High-Performance Modeling Week 4: Model Analysis Week 5: Interpretability

Lesson 4

Week 1: Model Serving Introduction Week 2: Model Serving Patterns and Infrastructures Week 3: Model Management and Delivery Week 4: Model Monitoring and Logginghttp://web.stanford.edu/~jacksonm/GTOC-II-Syllabus.html

Cryptography with Dan Boneh

Penetration Testing, Incident Response and Forensics

Security Analyst Fundamentals Specialization

Penetration Testing

Incident Response

Digital Forensics

Introduction to Scripting

Game Theory I

Game Theory II: Advanced Applications

Mechanism Design

Efficient Mechanisms

Auctions

Machine Learning Engineering for Production (MLOps) Specialization

Lesson 1

Week 1: Overview of the ML Lifecycle and Deployment Week 2: Selecting and Training a Model Week 3: Data Definition and Baseline

Lesson 2

Week 1: Collecting, Labeling, and Validating data Week 2: Feature Engineering, Transformation, and Selection Week 3: Data Journey and Data Storage Week 4: Advanced Data Labeling Methods, Data Augmentation, and Preprocessing Different Data Types

Lesson 3

Week 1: Neural Architecture Search Week 2: Model Resource Management Techniques Week 3: High-Performance Modeling Week 4: Model Analysis Week 5: Interpretability

Lesson 4

Week 1: Model Serving Introduction Week 2: Model Serving Patterns and Infrastructures Week 3: Model Management and Delivery Week 4: Model Monitoring and Logginghttp://web.stanford.edu/~jacksonm/GTOC-II-Syllabus.html

Cryptography with Dan Boneh

Penetration Testing, Incident Response and Forensics

Security Analyst Fundamentals Specialization

Penetration Testing

Incident Response

Digital Forensics

Introduction to Scripting

Game Theory I

Game Theory II: Advanced Applications

Social Choice

Mechanism Design

Efficient Mechanisms

Auctions

Machine Learning Engineering for Production (MLOps) Specialization

Lesson 1

Week 1: Overview of the ML Lifecycle and Deployment Week 2: Selecting and Training a Model Week 3: Data Definition and Baseline

Lesson 2

Week 1: Collecting, Labeling, and Validating data Week 2: Feature Engineering, Transformation, and Selection Week 3: Data Journey and Data Storage Week 4: Advanced Data Labeling Methods, Data Augmentation, and Preprocessing Different Data Types

Lesson 3

Week 1: Neural Architecture Search Week 2: Model Resource Management Techniques Week 3: High-Performance Modeling Week 4: Model Analysis Week 5: Interpretability

Lesson 4

Week 1: Model Serving Introduction Week 2: Model Serving Patterns and Infrastructures Week 3: Model Management and Delivery Week 4: Model Monitoring and Logginghttp://web.stanford.edu/~jacksonm/GTOC-II-Syllabus.html