Deep Learning in Business
The course provides comprehensive coverage of AI and ML's increasing integration, structured into three sections focusing on business strategy, fundamental technologies, and hands-on projects, to aid in strategy development and technical planning.
Description for Deep Learning in Business
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by Yonsei University
Duration: 3 weeks at 2 hours a week
Schedule: Flexible
Pricing for Deep Learning in Business
Use Cases for Deep Learning in Business
FAQs for Deep Learning in Business
Reviews for Deep Learning in Business
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Deep Learning in Business
Learn to apply advanced machine learning and deep learning models to real-world challenges by immersing yourself in the cutting-edge world of AI-powered finance and insurance.
A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.
In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.
Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.
The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.
From fundamental concepts to advanced methods such as deep learning and ensemble techniques, this program provides a comprehensive examination of machine learning techniques.
A program that emphasizes the practical implementation of data science and machine learning to overcome obstacles through the use of Python.
In-depth study of the applications of machine learning and computer vision, as well as practical experience in data analysis and Python programming.
Featured Tools
Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.
To address OpenAI Gym challenges and real-world problems, this course offers pragmatic artificial intelligence methods like Genetic Algorithms, Q-Learning, and neural network implementation.
Discover AI terminology, ethical norms, and protocols for responsibly utilizing and citing Generative AI.
A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.
An extensive study of the applications of AI in marketing, ranging from competitive analysis to content optimization and conversion enhancement.