Artificial Intelligence, or AI, and the Machine Learning that drives it, is one of most exciting new frontiers of technology being presented in the cloud today. Machine learning encompasses many different ideas, programming languages, frameworks, and approaches to the subject. Students from this course will be able to analyze the requirements for AI solutions, recommend appropriate tools and technologies that meet scalability and performance requirements.
Building Clustering Models with scikit-learn, you will gain the ability to enumerate different types of clustering algorithms and correctly implement them.
This course is a step-up to the Data Science with Python. This course will cover concepts to machine learning and you will learn how to build models using Frameworks like scikit-learn and SageMaker. No prior experience with ML is needed, however, we prefer candidates with the below knowledges:
1. Statistics, Calculus, Linear Algebra and Probability
2. Basic Python Programming Knowledge
3. Basic Data Modeling Concepts
Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course
Technologists curious about how deep learning really works
Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you'll need to meet the prerequisite
Students translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions.
Students design and implement AI apps and agents that use cloud services.
Students can then recommend solutions that use open source technologies.
Students will understand the components that make the AI portfolio and the available data storage options.
Module 1: Introduction to Machine Learning
Module 2: ML Concepts
Module 3: Data
Module 4: ML Algorithms
Module 5: Deep Learning Algorithms
Module 6: Model Performance and Optimization
Module 7: ML Frameworks
Module 8: AWS SageMaker
Module 9: AWS SageMaker Build
Module 10: AWS SageMaker Trainning
Module 11: AWS SageMaker Deploy
Machine Learning Data Analyst, Artificial Intelligence Data Scientist, Business Intelligence Data Analyst, Machine Learning Engineer, Data Analyst, Machine Learning Scientist