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Course Outline
Introduction to AWS Cloud9 for Data Science
- Overview of AWS Cloud9 capabilities relevant to data science.
- Setting up a data science environment in AWS Cloud9.
- Configuring Cloud9 for Python, R, and Jupyter Notebook usage.
Data Ingestion and Preparation
- Importing and cleaning data from diverse sources.
- Leveraging AWS S3 for data storage and retrieval.
- Preparing data for analytical and modeling tasks.
Data Analysis in AWS Cloud9
- Conducting exploratory data analysis with Python and R.
- Utilizing Pandas, NumPy, and data visualization libraries.
- Performing statistical analysis and hypothesis testing within Cloud9.
Machine Learning Model Development
- Creating machine learning models using Scikit-learn and TensorFlow.
- Training and assessing models in AWS Cloud9.
- Employing SageMaker alongside Cloud9 for large-scale model development.
Database Integration and Management
- Connecting AWS RDS and Redshift to AWS Cloud9.
- Querying extensive datasets via SQL and Python.
- Managing big data through AWS services.
Model Deployment and Optimization
- Deploying machine learning models via AWS Lambda.
- Automating deployment processes using AWS CloudFormation.
- Enhancing data pipelines for improved performance and cost-effectiveness.
Collaborative Development and Security
- Collaborating on data science projects within Cloud9.
- Using Git for version control and project management.
- Implementing security best practices for data and models in AWS Cloud9.
Summary and Next Steps
Requirements
- A foundational grasp of data science principles.
- Working knowledge of Python programming.
- Familiarity with cloud environments and AWS services.
Target Audience
- Data scientists.
- Data analysts.
- Machine learning engineers.
28 Hours
Testimonials (2)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
Nazeera Mohamad - Ministry of Science, Technology and Innovation
Course - Introduction to Data Science and AI using Python
I've find out new interesting things about Lambda and Serverless