ISSAI - Institute of Smart Systems and Artificial Intelligence

World-Class AI Education

ISSAI: Advanced AI Educational Ecosystem

Empowering the Next Generation of AI Leaders and Engineers

At ISSAI, we don't just teach AI; we build it. Our curriculum is designed by world-class researchers to take you from foundational concepts to deploying sophisticated Large Language Models (LLMs) on supercomputing infrastructure.

Explore Our Programs

Choose the program that matches your career goals and experience level

AI Foundations

1 Month • ~24-28 Hours in total

3x / week (2 hrs)

Analysts, AI Beginners

Online, Offline, Hybrid

See the modules

Research Experience (REP)

2 Months • 100 Hours in total

Each week day

Data Scientists, ML Engineers, Computer Engineers

Online, Offline, Hybrid

2.5M ₸ per person

See the modules

AI Product Management

1 Month • 48 Hours in total

3x / week (2 hrs)

Analysts, AI Beginners

Online, Offline, Hybrid

1.5M ₸ per person

See the modules

Executive & Short-Form Programs

GenAI: Productivity

Immediate workplace transformation. We teach your entire staff to use AI agents for 10x faster report writing, coding, and administrative automation.

1 Day • 2 Hours

One-time

All Staff & Corporate Teams

Online, Offline, Hybrid

AI for Decision Makers

Strategic AI integration. We move past the hype to discuss cost-to-value ratios, On-Premise vs. Cloud infrastructure, and building a data-driven culture.

2 Days • 16 Hours

Intensive

C-Level, VPs, Owners

Offline only

Customized Corporate Solutions

Your Challenges, Our Expertise.

We recognize that every organization has a unique "Digital Maturity." ISSAI offers specialized services to bridge your specific gaps:

Digital Maturity Assessment

Before we teach, we evaluate. We audit your current data infrastructure, technical talent, and hardware readiness to build a customized training roadmap.

Custom Curriculum Design

Need a course specifically on AI for Oil & Gas? Or AI for Fintech? We can tailor any of our modules or build new ones from scratch to solve your industry-specific problems.

Pilot Collaboration

We offer the possibility of continuing the training as a joint R&D pilot project, moving your course prototype into a real-world production environment.

Detailed modules

Choose the program that matches your career goals and experience level

AI Foundations & Applications

This course is designed for professionals looking to understand the breadth of AI and its industry-specific applications.

1 Month • ~24-28 Hours in total

3x / week (2 hrs)

Module 1: The AI Paradigm Shift

An exploration of AI history, the difference between symbolic AI and connectionism, and the socio-economic impact of automation.

Module 2: Data Engineering & Governance

The lifecycle of "Gold Standard" datasets. Understanding ETL pipelines, data cleaning, and the ethics of data bias.

Module 3: Mathematical Foundations of ML & DL

A deep dive into supervised, unsupervised, and reinforcement learning. Neural network architectures and backpropagation.

Module 4: Computer Vision (CV) Excellence

From edge detection to Vision Transformers (ViTs). Practical implementation of object detection (YOLO) and segmentation.

Module 5: Speech Technologies & Acoustics

Digital signal processing, ASR, and Text-to-Speech with a focus on low-resource and Turkic languages.

Module 6: Natural Language Processing (NLP)

Evolution from N-grams to Transformers. Text classification, NER, and attention mechanisms.

Module 7: AR Extended Reality (XR)

Integrating spatial computing with AI for gesture recognition and 3D reconstruction.

Module 8: High Performance Infrastructure

Architecting for scale. Understanding GPU interconnects and hardware requirements for modern AI.

Module 9: Generative AI Ecosystem

The rise of GANs, VAEs, and Diffusion Models. Understanding latent space for creative generation.

Module 10: Large Language Models (LLM)

Pre-training vs. Instruction Tuning. Analysis of GPT, Llama, and BERT architectures.

Module 11: Prompt Engineering & Reasoning

Advanced prompting: Chain-of-Thought, Tree-of-Thought, and ReAct frameworks.

Module 12: Multimodal Media Generation

Generating high-fidelity images and video from text. Ethics of deepfakes.

Module 13: AI Tooling & Integration

Practical workflows using Hugging Face, LangChain, and vector databases.

Module 14: Capstone Project

The development of a production-ready AI prototype mentored by ISSAI researchers.

Research Experience (REP)

2 Months • 2 hours per week day

Each week day

Access to the ISSAI’s supercomputer infrastructure

Phase 1: Fundamental R&D (Weeks 1-4)

Week 1: Data Synthesis & Benchmarking

Learning to generate high-quality synthetic data for domains where data is scarce. Setting up evaluation benchmarks.

Week 2: Advanced Evaluation (LLM-as-a-Judge)

Implementation of automated evaluation pipelines where one LLM critiques another using multi-dimensional rubrics.

Week 3: Full-Parameter Fine-Tuning

Hands-on training on the DGX A100 cluster. Managing gradients, optimizer states, and memory for full-model adaptation.

Week 4: Parameter-Efficient Fine-Tuning (PEFT/LoRA)

Deep dive into Low−RankAdaptation. Learning to adapt models with 1% of the trainable parameters while maintaining 99% performance.

Phase 2: Production & Deployment (Weeks 5-8)

Week 5: Vision-Language Models (VLM)

Training models that process interleaved text and images (e.g., InternVL). Applications in medical imaging and security.

Week 6: Retrieval-Augmented Generation (RAG)

Designing vector search architectures to connect LLMs to private corporate knowledge bases, solving the "hallucination" problem.

Week 7: High-Throughput Serving:

Optimizing inference using vLLM and LMDeploy. Implementing Continuous Batching and PagedAttention for production-grade APIs.

Week 8: LLMOps & Lifecycle Management:

The final frontier—monitoring model drift, versioning datasets, and automating the retraining pipeline.

AI Product Management

1 Month • 48 Hours in total

3x / week (2 hrs)

Phase 1: Strategic Foundations

AI Lifecycle Management

Understanding the CRISP-DM for AI and how it differs from traditional Software Development Life Cycles (SDLC).

Technical Specification (TZ)

Learning to write technical requirements that account for the probabilistic nature of AI (unlike the deterministic nature of standard code).

ROI & Ethics

Assessing the business value of AI projects. Addressing data privacy (GDPR/Local laws) and AI explainability.

Phase 2: The Leadership Role-Play

In a unique educational format, PM students manage the technical students from the Research Experience Program.

Managing Uncertainty

Leading "Daily Stand-ups" where models may fail to converge.

Stakeholder Communication

Translating technical metrics like Perplexity and F1−Score into business outcomes like "User Retention" and "Cost Savings."

Final Roadmap

Creating a comprehensive plan for internal AI adoption within your organization.

Ready to Start Your AI Journey?

Join hundreds of professionals who have transformed their careers with ISSAI's world-class AI education.