
CAREER TRACK
Forward Deployed Engineer Career Track
Forward Deployed Engineer
100% LIVE Interactive Classes
Forward Deployed Engineer

100% LIVE Interactive Classes
Reserve your spot today!
Basic Info
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Application closes on:14 Aug 2026
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What is in it for you?
100% Live Classes
Instructor-led Live Sessions
Attend 4 weeks of instructor led live classes from the top 1% industry experts
Projects & Case Studies
Projects & Case Studies
Gain hands-on experience with projects and real-world case studies for impactful learning.
Verified Certificate
Verified Certificate
Earn a industry recognized certificate and kick start your career
Session Recordings
Session Recordings
Revisit older chapters anytime with recorded sessions
Flexible Schedule
Flexible Schedule
Choose live classes from different cohorts that fit your availability.
Hands-on Lab Access
Hands-on Lab Access
Students get access to labs to practice their learnings
100% Moneyback Guarantee
Grab your slot before the offer expires
Reserve your spot today!
Basic Info
Select Offers
Application closes on:14 Aug 2026
Get instant access of pre-course material!
Talk to Us
We’re here to help! Reach us at:
Learn from Top 1%
Sr. Managers, VPs, CXOs, Directors & Founders from companies shaping the future.

Combo Offers
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100% Moneyback Guarantee
Available in 4 monthly installments at $600/month
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Curriculum
Duration: 24 weeks
Max Batch Size: 15 persons
Live Sessions Schedule
Sat - Sun (Weekends Only)
Timing 7:00 AM - 9:00 AM / 8:30 AM - 10:30 AM / 11:00 AM - 1:00 PM / 5:00 PM - 7:00 PM / 7:30 PM - 9:30 PM EST
- Setting up Python and choosing an IDE
- Basic syntax and data types
- Variables and operators
- Input/output operations
- Basic string operations
- Writing your first program
- Best practices for code formatting (PEP 8)
Mentors

12+ Years, Ex-Amazon, Startup Founding Team

22+ Years, Principal Engineer, IBM Research

20+ Years, Ex-Microsoft, Ex-Morgan Stanley

15+ Years, VP Product Lenskart, Ex-IIFL, Ex-Builder.ai
Course Includes
LIVE Interactive Sessions
Quizzes, Assignments & Projects
Study Materials & Session Recordings
Lab Access
Certificate
Tools Covered
Course Includes
LIVE Interactive Sessions
Quizzes, Assignments & Projects
Study Materials & Session Recordings
Lab Access
Certificate
Course Pre-requisites
Basic familiarity with any programming language
Comfort using a computer terminal
No prior cloud or AI experience needed
No prior DevOps experience required
Outcomes
Build and deploy production-grade Python applications and FastAPI services following PEP 8, OOP, and async programming best practices
Design and implement highly available, multi-region AWS and Azure architectures covering compute, storage, networking, and database services
Develop, fine-tune, and deploy LLM-powered applications including RAG pipelines, AI agents, and multimodal systems using LangChain, LlamaIndex, and Hugging Face
Containerize and orchestrate microservices using Docker and Kubernetes, and automate infrastructure provisioning with Terraform, Ansible, and Jenkins CI/CD pipelines
Architect and operate end-to-end MLOps and LLMOps platforms covering experiment tracking, model serving, drift detection, and agent observability with tools like MLflow, Langfuse, and Airflow
Define AI product strategy, write PRDs and agent scoping documents, and apply evaluation frameworks to measure and improve AI product quality and business impact
Projects You Will Build
Practical, enterprise-grade projects that reflect real industry challenges
Intelligent Document Q&A Platform on AWS
Build a production RAG application where enterprise users query a private document corpus via a FastAPI backend deployed on AWS EC2 behind an Application Load Balancer with Auto Scaling. Implement chunking strategies, vector storage with Pinecone, and LangChain orchestration, then containerize the stack with Docker and monitor latency and cost using CloudWatch. Deliverables include a GitHub repo, architecture diagram, and a benchmark report showing retrieval accuracy above 85% and p95 API latency under 500 ms.
Multi-Cloud AI Agent Deployment Pipeline
Design and ship a LangGraph-based AI agent that automates IT operations tasks, provisioned on Azure using Terraform and deployed through a Jenkins CI/CD pipeline with Ansible configuration management. The agent uses MCP tool calling, Langfuse observability, and a Kubernetes-hosted inference endpoint serving a quantized open-source LLM via llama.cpp. Deliverables include a fully automated IaC repo, a Grafana dashboard tracking agent success rate and token cost, and a runbook for rollback and retraining triggers.
End-to-End MLOps Platform for a Recommendation Model
Implement a complete MLOps lifecycle for a content recommendation model: version datasets with DVC, track experiments with MLflow, orchestrate retraining pipelines with Apache Airflow, and serve predictions via a FastAPI endpoint monitored with Prometheus and Grafana. Feature engineering is managed through Feast, embeddings are stored in a FAISS vector database, and the entire system is containerized and deployed to AWS using GitHub Actions CI/CD with automated rollback on metric regression. Deliverables include a reproducible pipeline repo, a model card, and an SLA report demonstrating model drift detection within 24 hours of distribution shift.

for successfully completing the 'Forward Deployed Engineer Career Track' course conducted from 26 Feb 2026 to 13 Aug 2026
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Networking
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for successfully completing the 'Forward Deployed Engineer Career Track' course conducted from 26 Feb 2026 to 13 Aug 2026

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Frequently Asked Questions
Everything you need to know about the course
You need only basic familiarity with any programming language and comfort using a terminal — no prior cloud, AI, or DevOps experience is required, as the track starts from Python fundamentals and builds up progressively.
The track spans nine courses covering Python programming, AWS and Azure architecture, Generative AI and LLM development, AI agent frameworks, Docker and Kubernetes, Jenkins/Terraform/Ansible, MLOps/LLMOps, and AI product management — giving you a full-stack view of modern AI engineering.
Expect to invest roughly 15–20 hours per week across live instructor-led classes, hands-on labs, and self-paced review — all sessions are interactive and scheduled so you can ask questions in real time.
A laptop with internet access is sufficient; all labs use cloud-based environments (AWS, Azure) and open-source tools like Docker, Python, and VS Code that run on Windows, macOS, or Linux without special hardware.
The track begins with Python basics including syntax, data types, and control flow, so even if your Python is rusty or you come from another language, you'll be brought up to speed before advancing to APIs, OOP, and async programming.
Graduates are positioned for roles such as Forward Deployed Engineer, AI/ML Engineer, MLOps Engineer, Cloud Solutions Architect, AI Agent Developer, and AI Product Manager — all high-demand positions at product companies and consultancies.
The Micro Degree course is an online LIVE course, where LIVE sessions will be conducted online on our Classroom platform. Prior to the start of the course, you'll receive preparatory material in the form of recorded content which can be access on the same platform.
In this course instructors will use English language for teaching.
Upon successful registration, you will receive a confirmation email on your registered email ID. In this email you will receive login details for your newly created account on the Edyoda Classroom platform (https://classroom.edyoda.com). Additionally, you will receive a PDF guide containing step-by-step instructions on how to utilize the platform to access live sessions and learning materials.
Our instructors are the industry experts with a minimum working experience of 10 years with a strong technical and teaching background. They bring industry knowledge and practical expertise to the course.
Yes, the course includes online assignments, quizzes, and a final project to reinforce your learning and assess your proficiency in Forward Deployed Engineer Career Track.
Yes, you can interact with instructors and fellow students through discussion forums, live Q&A sessions. We encourage a supportive learning community.
Yes, hands-on lab access is available at an additional cost, typically around ₹2,750 (or $30 for international learners) per year. This is the standard rate for most tracks, though specialized labs such as Data and Security may be priced differently. Beyond just practicing what you learn, the labs let you host and showcase your projects live, so you can share your work on social media or present it directly to recruiters as part of your portfolio.
We offer a 100% money-back guarantee to ensure your complete satisfaction. If you're not satisfied, you can request a full refund within 3 days of purchase or before the second session, whichever comes earlier. Simply contact our support team(support@edyoda.com) with your purchase details, such as the order ID or email address, and share your reason for the refund. Requests made after 3 days or after the second session will not be eligible for a refund. There are no hidden charges, you will receive the full amount paid. Refunds are processed within 7–10 business days and credited back to your original payment method.
