Mastering AI : From ML to Automation
This course provides learners with the necessary skills to utilize AI tools for innovation, automation, and decision-making, with an emphasis on the principles and applications of AI.
Description for Mastering AI : From ML to Automation
Comprehensive AI Fundamentals: Acquire an understanding of the fundamental principles of artificial intelligence and its transformative influence on sectors including finance, healthcare, and robotics.
Machine Learning Expertise: Explore deep learning, decision trees, neural networks, and predictive modeling, as well as supervised and unsupervised learning.
Applications of Reinforcement Learning: Develop an understanding of the decision-making process of intelligent agents in dynamic environments by utilizing algorithms that are intended to optimize long-term results.
AI in Robotics and Automation: Acquire a deeper understanding of the ways in which AI-driven robotics and automation are transforming processes, facilitating real-time interaction with the environment.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Udemy provided by Ndiaga Fall
Duration: 6h 37m
Schedule: Full lifetime access
Pricing for Mastering AI : From ML to Automation
Use Cases for Mastering AI : From ML to Automation
FAQs for Mastering AI : From ML to Automation
Reviews for Mastering AI : From ML to Automation
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Mastering AI : From ML to Automation
Featured Tools
Explore the ethical implications of AI by investigating frameworks, industry best practices, and real-world obstacles.
This course will provide you with an understanding of the technical underpinnings and essential terminology associated with generative artificial intelligence (AI).
Genome sequencing, disease gene discovery, computational Tree of Life construction, bioinformatics' impact on current biology, computational biology software, and an Honors Track for software programming and algorithm implementation are covered in the course.
Begin your professional journey as a cybersecurity analyst. Develop the necessary skills for a vocation in cybersecurity that is in high demand in as little as six months. No prior experience is necessary to initiate the process.
Construct the gradient descent algorithm, execute univariate linear regression with NumPy and Python, and create data visualizations with matplotlib.