Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AWS Cloud9 for Data Science
- Key features of AWS Cloud9 relevant to data science
- Initializing a data science workspace in AWS Cloud9
- Setting up Cloud9 for Python, R, and Jupyter Notebook usage
Data Ingestion and Preparation
- Importing and cleansing data from diverse sources
- Leveraging AWS S3 for secure data storage and access
- Preparing data for analytical and modeling purposes
Data Analysis in AWS Cloud9
- Conducting exploratory data analysis with Python and R
- Utilizing Pandas, NumPy, and visualization libraries for insights
- Performing statistical analysis and hypothesis testing within Cloud9
Machine Learning Model Development
- Creating machine learning models using Scikit-learn and TensorFlow
- Training and assessing model performance in AWS Cloud9
- Integrating SageMaker with Cloud9 for large-scale model development
Database Integration and Management
- Connecting AWS RDS and Redshift to AWS Cloud9 environments
- Querying extensive datasets using SQL and Python
- Managing big data workloads with AWS services
Model Deployment and Optimization
- Deploying machine learning models via AWS Lambda
- Automating deployment processes with AWS CloudFormation
- Tuning data pipelines for optimal performance and cost efficiency
Collaborative Development and Security
- Facilitating collaboration on data science projects in Cloud9
- Implementing Git for version control and project management
- Applying security best practices for data and models in AWS Cloud9
Summary and Next Steps
Requirements
- Foundational knowledge of core data science concepts
- Working familiarity with Python programming
- Practical experience 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
