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コース概要
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
要求
- 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 時間
お客様の声 (3)
Understanding big data beter
Shaune Dennis - Vodacom
コース - Big Data Business Intelligence for Telecom and Communication Service Providers
All good, nothing to improve
Ievgen Vinchyk - GE Medical Systems Polska Sp. Z O.O.
コース - AWS Lambda for Developers
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