AI-First Data Scientist Program
Foundation Model + Custom Solution Designer
Become the modern data scientist who blends classic ML with LLM hybrid solutions.
Classic 'data scientist' definition is outdated; no one trains foundation-model + custom-solution hybrids. Covers modern DS workflow (Polars, DuckDB), foundation model fine-tuning, sentence transformers, time series + LLM hybrid, causal inference + LLM, synthetic data generation and LLM-as-feature-extractor.
Quick Facts
Why This Program for Your Company
Talent Development
Grow your in-house teams; reduce vendor and outsourcing dependency
Fast Time-to-Value
Built for a 90-day pilot-to-production trajectory
Measurable ROI
Before/after capability report + KPI dashboard with tangible outcomes
AI Culture
AI adoption across all levels — from executive to engineer
Delivery Models
Choose the delivery format that fits your team
On-site
At your company location, closed group
Hybrid
Online + periodic in-person intensives
Fully Remote
Live remote + recordings + lab notebooks
Train-the-Trainer
Build in-house trainers — long-term scaling
Tailored to Your Company
Content is customized to your industry, regulatory framework, existing tech stack and target use cases. Labs run on your existing systems or sample datasets.
Lab Environment
Hands-on labs run on your company data (under NDA), isolated sandbox or sample dataset
Post-Training Support
30 days async support (Slack/Teams/Discord) + optional monthly follow-up sessions + code review support
Why Now? — Türkiye's Empty Market
Academic DS training exists, modern hybrid practice doesn't. Trendyol/Garanti/Migros DS teams are building this profile.
About the Program
Target Teams
- Existing data scientists
- ML engineers
- Quant analysts
- PhD researchers
Your Team's Outcomes
- 3x productivity with modern DS workflow
- Foundation model fine-tuning (LoRA, QLoRA, full FT)
- Time series + LLM hybrid forecasting
- Synthetic data generation pipelines
- Use LLM as feature extractor
Prerequisites
- Advanced Python
- Classic ML experience
- PyTorch or TensorFlow
Trainings in this Program
12 modules / micro-trainings
- 01
Modern DS Workflow (Polars, DuckDB, Marimo)
- 02
Feature Engineering Refresh
- 03
AutoML Strategies
- 04
Foundation Model Fine-tuning
- 05
Sentence Transformers
- 06
Time Series + LLM Hybrid
- 07
Causal Inference + LLM
- 08
Synthetic Data Generation
- 09
Advanced A/B Testing
- 10
ML Interpretability (SHAP, LIME)
- 11
LLM as Feature Extractor
- 12
Capstone: Hybrid ML + LLM Solution
Capstone Project
Hybrid solution for a real ML problem combining classic ML + foundation model — with eval, ablation study and production deployment.
How We Work
From discovery to delivery and post-training follow-up
- 1
Discovery
Free 30min — team capability map, use case discovery, goal setting
- 2
Design
Custom curriculum, lab scenarios and delivery timeline for your use cases
- 3
Delivery
Live training + hands-on labs + capstone project + completion certificate
- 4
Follow-up
Capability report + 30-day support + optional monthly check-in sessions
Career Path
Positions you can target after this program
Tech Stack & Topics
Frequently Asked Questions
How do enrollment and participant selection work?
How is pricing structured?
Can the curriculum be customized for our use cases?
On-site or remote?
Is post-training support included?
Are certificates provided?
Who is this program for?
What will I learn?
What is the duration and format?
What are the prerequisites?
Which positions does this program prepare me for?
Why is this program needed in Türkiye?
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Bring This Program to Your Team
In a free 30-minute discovery call we map your team's capability, explore your target use cases and prepare a custom quote for your company. No commitment.