Aim

This program is designed to give participants advanced skills in building scalable data pipelines, managing large datasets, and preparing data for AI models. The focus is on practical data engineering techniques that drive AI solutions, ensuring smooth data flow, storage, and processing both on the cloud and on-premise.

Program Objectives

• Master Core Data Engineering for AI: Gain a solid understanding of the core principles that underpin data engineering in AI.
• Build Scalable Pipelines: Learn how to design and automate ETL workflows for handling large-scale data.
• Efficient Data Management: Develop expertise in managing, storing, and processing structured and unstructured data effectively.
• Real-Time Data Processing: Implement real-time data streaming solutions for AI models.
• Hands-On Cloud Experience: Work with top cloud-based data tools to streamline AI workflows.

Participant’s Eligibility

• Data Engineers looking to design and manage data pipelines for AI.
• Machine Learning Engineers aiming to handle large datasets efficiently.
• AI Researchers focusing on optimizing data flows for AI models.
• Data Scientists interested in mastering data preparation for machine learning.

Program Outcomes

• Scalable Pipeline Expertise: Master the design and automation of scalable data pipelines for AI.
• Cloud Data Mastery: Proficiency in using cloud tools and big data solutions to manage large AI datasets.
• Real-Time Data Skills: Ability to implement and manage real-time data streams for AI models.
• Data Preparation Mastery: Deep understanding of cleaning, transforming, and optimizing data for machine learning.

Program Deliverables

• e-LMS Access: Online platform with all course content and materials.
• Real-Time Project: Practical project focusing on building and managing AI-driven data pipelines.
• Guidance and Mentorship: Support from experts for project completion.
• Certification: Earn certification after completing all required assignments and exams.

Future Career Prospects

• Data Engineer for AI: Build data infrastructure to support AI and machine learning applications.
• Cloud Data Architect: Manage and design cloud data systems for AI-driven solutions.
• Machine Learning Data Engineer: Optimize data flows for machine learning models.
• Big Data Engineer: Handle large-scale data environments for AI applications.
• Data Pipeline Engineer: Develop and maintain data pipelines for real-time AI models.
• AI Infrastructure Engineer: Design robust data infrastructure to support AI at scale.

Job Opportunities

• AI-Focused Organizations: Build large-scale AI and machine learning systems.
• Cloud Computing Firms: Provide infrastructure for AI and data management.
• Startups: Create scalable data pipelines for real-time AI-driven solutions.
• Enterprises: Support big data and AI-powered decision-making processes.