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Agile Fever

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About Agile Fever

Location: Online

Courses

Agentic AI Bootcamp

Cost: $2,000
Duration: 6 weeks
Locations: Online
Course Description:

6 Weeks(Monday-Thursday): 48 Hours | 2 Hours/Day
6 Weeks(Saturday-Sunday): 48 Hours | 4 Hours/Day

Agentic AI is transforming the way LLMs are used, moving away from prompt-based
interfaces and toward autonomous agents capable of reasoning, planning, tool usage, and
collaboration. This 48-hour BootCamp provides you with hands-on experience building
and deploying next-generation technologies.
You will receive practical experience with CrewAI, LangGraph, and AutoGen frameworks.

From memory and planning to infrastructure and SaaS deployment, you’ll work on real-
world applications such as CRMs, travel bots, and scheduling assistants—all in production-
ready settings.

AI and ML Bootcamp

Cost: $3,000
Duration: 12 weeks
Locations: Online
Course Description:

12 Weeks(Monday-Thursday): 96 Hours | 2 Hours/Day
12 Weeks(Satur-Sun): 96 Hours | 4 Hours/Day

Advance into the future of tech with AgileFever’s AI and ML BootCamp, an elite, live
training experience designed to help professionals transition into high-impact AI and ML
roles. This isn’t a theory-heavy course. It’s a practical, 80-hours, 100% live-trainer-led
program built for real-world implementation from day one.

Learn to build and deploy intelligent systems using tools like TensorFlow, PyTorch, Scikit-
learn, Hugging Face, OpenCV, and more. From foundational statistics to deep learning,

LLMs, NLP, and computer vision, you will work hands-on across the entire AI pipeline.
Every module is taught by top-tier instructors from FAANG and global tech firms, ensuring
you don’t just learn AI, but practice it the way companies do with 15 real time projects.

This BootCamp is ideal for engineers, analysts, and developers looking to upskill with job-
ready AI capabilities, real projects, and personalized career support.

Data Engineer BootCamp

Duration: 22 weeks
Locations: Online
Course Description:

Data engineering is the unsung hero that drives AI, analytics, and business choices. Data
Engineer BootCamp course will teach you the tools and strategies for collecting, moving,
and transforming vast volumes of data across platforms.
From learning the fundamentals of data flow to the developing ETL processes on cloud
platforms, you will get hands-on experience with actual technologies like Spark, Hadoop,
Airflow, and others. This bootcamp simplifies pipeline development for batch or stream
processing. Learn how top IT teams build, grow, and manage their data architecture and
prepare to use the same skills at work.

Gen AI Bootcamp

Cost: $3,000
Duration: 11 weeks
Locations: Online
Course Description:

11 Weeks(Monday-Thursday): 88 Hours | 2 Hours/Day
11 Weeks(Saturday-Sunday): 88 Hours | 4 Hours/Day

AgileFever’s Generative AI BootCamp is a 70-hour live, instructor-led program designed for professionals
looking to create, fine-tune, and deploy GenAI-powered apps. Whether you are dealing with
LLMs, transformers, or retrieval-augmented generation (RAG), this BootCamp will teach you actual skills, not
just theory. You will be able to work with real data, real models, and production-ready processes.
You will hear from industry professionals who have firsthand experience deploying GenAI systems at
MAANG and AI-first organisations. Every session is live, interactive, and supported with projects that lead
straight to portfolio-ready work.

MLOps BootCamp

Cost: $2,000
Duration: 4 weeks
Locations: Online
Course Description:

Weekdays(Monday-Thursday): 50 Hours | 2 Hours/Day for 25 Days

AgileFever’s 50-hour live-led MLOps BootCamp delivers Machine Learning
Operations (MLOps). Built for practitioners who want to manage the whole ML lifecycle,
from data intake to CI/CD, model monitoring, and deployment.

Learn about GCP Vertex AI, as well as how to develop production-grade pipelines using
industry-standard technologies. This is not just a theory; it is practical MLOps training for
engineers, data scientists, and DevOps professionals who want to lead scalable ML
efforts.

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