How Can ArchAI Help Your Enterprise
AI ACADMEY
Perception-Enabled AI Learning
Designed to move beyond theory, ArchAI Academy helps you understand how intelligent systems see and interpret the world. Through real-world data, computer vision demos, and hands-on labs, you’ll learn to build perception-enabled AI models that make decisions with awareness, efficiency, and safety.
Enterprise & Corporate Teams
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Strategic AI Overview
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AI/ML landscape, trends, and enterprise use cases
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Aligning AI initiatives with business goals and KPIs
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Technical Foundations (at Appropriate Depth)
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UNIX, Python, Conda environments for technical participants
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GPU usage and scalable environments (local vs. cloud)
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Classical & Modern ML
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Building and validating models on real corporate-style datasets
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Experimentation with multiple algorithms and model comparison
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Deep Learning & LLMs in Production
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Applying deep learning to images, text, and structured data
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Using and integrating LLMs for knowledge retrieval, automation, support
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Deployment, APIs & MLOps Concepts
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Creating, testing, and deploying model APIs
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Versioning, monitoring, logging, and basic MLOps lifecycle
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Domain-Specific Labs
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Sector-focused case studies (e.g., banking risk scoring, fraud detection, warranty claims, call-center AI)
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Applying best practices to their own use cases
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Risk, Governance & Compliance
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Model risk management, explainability basics
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Data governance and regulatory considerations
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Enterprise & Corporate Teams
Corporate teams need AI skills that are serious, robust, and aligned with business outcomes. This track is designed for mixed audiences—technical staff, analysts, and decision-makers—who want to move beyond buzzwords and deliver real value.
We cover the full journey: from data and environment setup to training, evaluating, and deploying models at scale. Teams experiment with classical ML and deep learning, explore LLM-based solutions, and learn how to integrate models via APIs into existing systems and workflows.
Sessions can be tailored by industry (banking, finance, healthcare, automotive, etc.), focusing on relevant case studieslike fraud detection, risk scoring, recommendation systems, or customer support automation. Governance, explainability, and compliance are integrated throughout, helping organizations innovate responsibly.
Enterprise and Corporate teams
End-to-end AI, from UNIX to deployment and LLMs.
what students will learn
What They’ll Learn
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Working confidently in UNIX terminals and managed environments
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Intermediate Python for data analysis and AI development
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Data manipulation and visualization using pandas and NumPy
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Classical machine learning: regression, classification, clustering
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Deep learning fundamentals and neural network training
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Generative AI and large language models via APIs
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Turning models into simple APIs and integrating them into applications
Students in this program will develop a strong, practical foundation in artificial intelligence by working through the full lifecycle of building AI systems. They will gain confidence working in technical environments, writing clean and maintainable Python code, and handling real datasets for analysis and modeling. Learners will explore classical machine learning techniques as well as modern deep learning and generative AI approaches, including large language models.
The program also introduces GPU-based tooling, model evaluation, and deployment concepts, helping students understand how AI systems are built and used in real applications. By the end of the course, students will be able to design, build, and present end-to-end AI projects.
course details
This is a hands-on, project-driven program designed for students who want serious technical depth and real-world experience.
Course Term
8 weeks
Format
In-person, small-group sessions with guided instruction and hands-on labs
Experience Level
Intermediate to advanced students with basic programming familiarity
Tools & Technologies
Python, UNIX, pandas, NumPy, GPU-enabled frameworks (e.g., PyTorch / TensorFlow), AI APIs
Course Fee
$499
Final Outcome
A completed end-to-end AI project suitable for portfolios, resumes, and interviews
