What does the Data Scientists and Serverless course cover?
Data Scientists and Serverless is covered here in 5 modules: Introduction to Serverless Computing: Benefits of serverless computing for data science, Serverless Data Pipelines, Containerization and Orchestration: Introduction to containerization using Docker and 2 more. The outline lists 16 specific topics, opening with what is serverless computing?
How do you approach Data Scientists and Serverless step by step?
The work is sequenced in 5 stages. It starts with Introduction to Serverless Computing: Benefits of serverless computing for data science, moves through Serverless Data Pipelines and Containerization and Orchestration: Introduction to containerization using Docker, and ends at Advanced Serverless Topics: Serverless monitoring and logging. Each stage carries its own topic list, so the sequence is followed rather than summarised.
What is in Module 1 of the Data Scientists and Serverless course?
Module 1 is Introduction to Serverless Computing: Benefits of serverless computing for data science. It works through what is serverless computing?, benefits of serverless computing for data science, serverless computing architectures and frameworks and 1 more. It sets the vocabulary the remaining 4 modules build on.
How is the Data Scientists and Serverless course delivered?
The Data Scientists and Serverless course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.
How much does the Data Scientists and Serverless course cost?
The Data Scientists and Serverless course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.
Closely related courses: Serverless Debuggability, Serverless for SREs, API Gateway and Serverless, Serverless in IT Strategy.
More answers: what you get with every course, refund policy, all help answers.
Data Scientists and Serverless; Revolutionizing Cloud Computing
Course Overview
Welcome to the Data Scientists and Serverless; Revolutionizing Cloud Computing course, where you will learn the fundamentals of serverless computing and how to apply them to real-world data science projects. This comprehensive course is designed to help data scientists and analysts leverage the power of serverless computing to build scalable, efficient, and cost-effective data pipelines.Course Objectives
- Understand the basics of serverless computing and its benefits for data science
- Learn how to design and implement serverless data pipelines using AWS Lambda, Google Cloud Functions, and Azure Functions
- Master the skills to deploy and manage serverless applications using containerization and orchestration tools
- Apply serverless computing to real-world data science projects, including data preprocessing, feature engineering, and model deployment
- Develop hands-on experience with popular data science tools and technologies, including Python, R, and SQL
Course Outline
Module 1. Introduction to Serverless Computing: Benefits of serverless computing for data science
- What is serverless computing?
- Benefits of serverless computing for data science
- Serverless computing architectures and frameworks
- Hands-on lab: Deploying a serverless application using AWS Lambda
Module 2: Serverless Data Pipelines
- Designing serverless data pipelines
- Implementing serverless data pipelines using AWS Glue and AWS Step Functions
- Hands-on lab: Building a serverless data pipeline using Google Cloud Functions and Cloud Dataflow
Module 3. Containerization and Orchestration: Introduction to containerization using Docker
- Introduction to containerization using Docker
- Orchestration using Kubernetes and serverless frameworks
- Hands-on lab: Deploying a containerized serverless application using Azure Functions and Kubernetes
Module 4. Serverless Data Science: Deploying machine learning models using serverless computing
- Applying serverless computing to data preprocessing and feature engineering
- Deploying machine learning models using serverless computing
- Hands-on lab: Building a serverless recommendation system using AWS SageMaker and AWS Lambda
Module 5. Advanced Serverless Topics: Serverless monitoring and logging
- Serverless security and access control
- Serverless monitoring and logging
- Hands-on lab: Implementing serverless security and monitoring using AWS IAM and AWS CloudWatch
Course Features
- Interactive and Engaging: Interactive labs, quizzes, and assignments to keep you engaged and motivated
- Comprehensive: Covers the fundamentals of serverless computing and its applications in data science
- Personalized: Personalized learning experience with tailored feedback and support
- Up-to-date: Course content is updated regularly to reflect the latest developments in serverless computing and data science
- Practical: Hands-on labs and projects to help you apply theoretical concepts to real-world problems
- Real-world Applications: Learn how to apply serverless computing to real-world data science projects and use cases
- High-quality Content: Course content is designed and delivered by expert instructors with extensive experience in serverless computing and data science
- Certification: Participants receive a certificate upon completion of the course
- Flexible Learning: Learn at your own pace and on your own schedule
- User-friendly: Easy-to-use interface and navigation
- Mobile-accessible: Access the course content on-the-go using your mobile device
- Community-driven: Join a community of learners and professionals to network and share knowledge
- Actionable Insights: Gain actionable insights and practical skills to apply to your work or projects
- Hands-on Projects: Work on hands-on projects to apply theoretical concepts to real-world problems
- Bite-sized Lessons: Bite-sized lessons and modules to help you learn in a flexible and efficient way
- Lifetime Access: Lifetime access to the course content and materials
- Gamification: Earn badges and points for completing modules and achieving milestones
- Progress Tracking: Track your progress and stay motivated with personalized feedback and support