Gen AI ASCEND Integrated - Data ML
Completed by Elakiyaa P on July 14, 2026
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Intermediate courses for Data ML
Learning objectives
- Apply generative AI models to enhance data engineering tasks such as architecture design, database querying, and ETL workflows.
- Implement data preparation techniques including cleaning, transformation, and feature engineering using AWS services for machine learning workloads.
- Ensure data integrity and ethical considerations in data engineering projects, addressing bias and securely handling sensitive information.
- Utilize AWS Glue, Glue DataBrew, and EMR to build scalable, production-ready data pipelines for machine learning applications.
Skills learned
- Extract, Transform, Load
- Convolutional Neural Networks
- Personally Identifiable Information
- Generative Model Architectures
- Snowflake Schema
- Star Schema
- AI Enablement
- Query Languages
- AWS SageMaker
- Responsible AI
- Artificial Intelligence
- Apache Spark
- Amazon Web Services
- Amazon S3
- Data Integrity
- Data Synthesis
- Generative AI
- Data Mining
- Data Preprocessing
- Feature Engineering
- Prompt Engineering
- Data Warehousing
- Data Cleansing
- Data Architecture
- Database Design
- Data Ethics
- Data Transformation
- Data Pipelines
- Data Security
- Data Infrastructure
- Data Quality
- Data Analysis
- Skills section collapsed. Showing 8 of 32 skills.
Learning content completed
Some of the content and skills presented have been contributed by the content provider.