This course explores advanced AI & ML techniques, ending with a comprehensive capstone project. You will learn about cutting-edge ML methods, ethical considerations in GenAI, and strategies for building scalable AI systems. The capstone project allows students to apply all their learned skills to solve a real-world problem.
Advanced AI and Machine Learning Techniques and Capstone
This course is part of Microsoft AI & ML Engineering Professional Certificate
Instructor: Microsoft
Sponsored by Coursera for Reliance Family
Recommended experience
Skills you'll gain
- Statistical Machine Learning
- Ethical Standards And Conduct
- Applied Machine Learning
- Microsoft Azure
- Cloud Computing
- Machine Learning Methods
- Data Governance
- Machine Learning Algorithms
- Data Ethics
- Cloud Services
- Cloud Platforms
- Artificial Intelligence and Machine Learning (AI/ML)
- Artificial Intelligence
- Machine Learning
- Cloud Solutions
- Computer Science
Details to know
Add to your LinkedIn profile
19 assignments
See how employees at top companies are mastering in-demand skills
Build your Software Development expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from Microsoft
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 4 modules in this course
This advanced module delves into cutting-edge methodologies that enhance the performance, efficiency, and privacy of ML systems. By the end of this module, you'll have hands-on experience with these advanced techniques, equipping you with the skills to tackle complex ML challenges and contribute to cutting-edge research and development.
What's included
2 videos17 readings10 assignments1 peer review
This module provides an in-depth exploration of the ethical and human-centric considerations essential to the development and deployment of AI and ML systems. By the end of this module, you'll be equipped to critically assess and address the ethical, human, and organizational challenges posed by AI technologies, ensuring that your work aligns with both technical excellence and societal values.
What's included
11 readings3 assignments
This module focuses on designing and implementing distributed computing solutions to handle large-scale ML challenges efficiently. This module equips you with the knowledge and skills needed to build and optimize ML systems for high-throughput and scalable environments. By the end of this module, you'll be adept at designing, implementing, and optimizing distributed ML systems that can efficiently tackle large-scale problems, while balancing performance and cost considerations to meet organizational and project needs.
What's included
12 readings5 assignments
This module provides a comprehensive exploration of the professional and strategic aspects of working as an AI/ML engineer within a corporate environment. It will guide you through the key responsibilities, ethical considerations, and strategic decision-making processes relevant to the field. By the end of this module, you will be well equipped to navigate your professional responsibilities, implement ethical AI practices, manage cost-performance trade-offs, and communicate effectively with stakeholders, positioning yourself as a valuable contributor in the corporate AI landscape.
What's included
1 video8 readings1 assignment
Why people choose Coursera for their career
Recommended if you're interested in Computer Science
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy