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
- Fundamental understanding of data science concepts.
- Familiarity with Python programming.
- Experience with cloud environments and AWS services.
Audience
- Data scientists.
- Data analysts.
- Machine learning engineers.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 5200 € + VAT*
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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
