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Course Outline
Introduction to AWS Cloud9 for Data Science
- Overview of AWS Cloud9 features for data science
- Setting up a data science environment in AWS Cloud9
- Configuring Cloud9 for Python, R, and Jupyter Notebook
Data Ingestion and Preparation
- Importing and cleaning data from various sources
- Using AWS S3 for data storage and access
- Preprocessing data for analysis and modeling
Data Analysis in AWS Cloud9
- Exploratory data analysis using Python and R
- Working with Pandas, NumPy, and data visualization libraries
- Statistical analysis and hypothesis testing in Cloud9
Machine Learning Model Development
- Building machine learning models using Scikit-learn and TensorFlow
- Training and evaluating models in AWS Cloud9
- Using SageMaker with Cloud9 for large-scale model development
Database Integration and Management
- Integrating AWS RDS and Redshift with AWS Cloud9
- Querying large datasets using SQL and Python
- Handling big data with AWS services
Model Deployment and Optimization
- Deploying machine learning models using AWS Lambda
- Using AWS CloudFormation to automate deployment
- Optimizing data pipelines for performance and cost-efficiency
Collaborative Development and Security
- Collaborating on data science projects in Cloud9
- Using Git for version control and project management
- Security best practices for data and models in AWS Cloud9
Summary and Next Steps
Requirements
- Basic understanding of data science concepts
- Familiarity with Python programming
- Experience with cloud environments and AWS services
Audience
- Data scientists
- Data analysts
- Machine learning engineers
28 Hours
Testimonials (4)
Amount of Information, Exercises
Lukasz Kowalski - Sii Sp. z o.o.
Course - AWS IoT Core
Machine Translated
All good, nothing to improve
Ievgen Vinchyk - GE Medical Systems Polska Sp. Z O.O.
Course - AWS Lambda for Developers
IOT applications
Palaniswamy Suresh Kumar - Makers' Academy
Course - Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core 「4 Hours Remote」
Later the balance between theory and practice was much better. But the beginnings were terrible. The way of expressing (language) is very calm, understandable, in a human way.
Lukasz Derkowski - NetworkedAssets Sp. z o.o.
Course - AWS CloudFormation
Machine Translated
