Requirements
- Comfortable with Python basics (functions, pandas)
- Working knowledge of SQL (joins, aggregations)
- Basic understanding of statistics and ML concepts (helpful, not mandatory)
- Laptop with stable internet; willingness to do assignments and a capstone
Features
- Live Project-Based Training
- Expert-Led Sessions
- Flexible Learning Options
- Interactive Learning
- Study Material
- One-on-One Mentorship
- Globally Recognized Certification
Target audiences
- Data analysts moving into data science/ML
- Data engineers who want Foundry + analytics workflows
- BI professionals shifting to governed, production analytics
- Fresh graduates with Python/SQL looking for Foundry-aligned skills
- Working professionals in ops, risk, supply chain, finance analytics
If your team is moving to Palantir Foundry, the fastest way to get value is to learn how data, logic, and models come together inside Foundry—not in theory, but in day-to-day workflows. Ascents Learning offers Palantir Foundry Data Science Training built around real project patterns: ingesting messy sources, building reusable transforms, modeling an Ontology, and shipping analytics that business users can trust.
In this Palantir Foundry Data Science Training, you’ll work with common Foundry building blocks (pipelines, code repos, notebooks, data lineage, access controls) and practice the “last mile” tasks that usually slow teams down: feature engineering from curated datasets, experiment tracking, model validation, and operationalizing outputs for stakeholders. Ascents Learning keeps it hands-on—weekly assignments, mentor reviews, and a capstone that mirrors how Foundry is used in production.
By the end, you’ll be able to build end-to-end solutions in Foundry: from raw ingestion to governed datasets, to ML-ready features, to deployed insights. If you’re comparing options, Ascents Learning focuses on practical delivery and job readiness through structured Palantir Foundry Data Science Training.
Curriculum
- 15 Sections
- 0 Lessons
- 10 Weeks
- Module 1: Foundry Fundamentals & Workspace Setup0
- Module 2: Data Ingestion Basics (Batch + Incremental Thinking)0
- Module 3: Data Profiling & Quality Checks0
- Module 4: Data Cleaning & Standardization in Transforms0
- Module 5: Building Curated Datasets & Data Modeling0
- Module 6: Pipeline Design & Dependency Management0
- Module 7: Working with Code Repositories (Team Workflow)0
- Module 8: Foundry Notebooks for Data Science Work0
- Module 9: Feature Engineering from Governed Data0
- Module 10: Ontology Basics (Business Context Layer)0
- Module 11: Ontology-Driven Analytics & Metrics0
- Module 12: Model Training Workflows Inside Foundry0
- Module 13: Experiment Tracking & Model Governance Habits0
- Module 14: Operationalizing Outputs (Production Thinking)0
- Module 15: Capstone Project + Interview Readiness0



