OCI Data Science Pro
Oracle Cloud Infrastructure 2024 Data Science Professional (1Z0-117)
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Cheat sheet
Keep the key ideas within reach.
ExploreKey terms
Get comfortable with the vocabulary.
ExploreStudy plan
Give each week a clear focus.
ExploreCommon mistakes
Understand the traps and how to avoid them.
ExploreCase studies
Put your knowledge to work in context.
ExploreExam-day guide
Prepare for the day ahead.
ExploreAbout this exam
The Oracle Cloud Infrastructure 2024 Data Science Professional credential, exam code 1Z0-117, is Oracle's professional-level certification for practitioners who build and operate machine learning workloads on OCI. It targets data scientists, ML engineers, and platform engineers who already work with OCI Data Science and want formal recognition of their ability to design projects, run training at scale, and keep models healthy in production. The exam spans four broad areas: data science concepts and how OCI Data Science fits together; projects, notebook sessions, and conda environments; model training with jobs plus the model catalog and deployments; and data access, pipelines, and MLOps operations. Expect scenario questions rather than pure recall - you will be asked to choose the right OCI construct for a given constraint, such as when to use a job instead of a notebook session, or how to wire a pipeline with artifacts and deployments. Preparation should be hands-on: create a project, launch a notebook session, publish and version a conda environment, run a training job, register a model, deploy it, and build a pipeline. Pair that lab work with Oracle University training and the official exam guide. Note: at the time of writing, the official exam page was unavailable for maintenance, so verify current logistics with Oracle University before booking. This page is independent study material and is not affiliated with or endorsed by Oracle.
What you'll study
About OCI Data Science Pro preparation
What is the exam format and how long do I get?
The official exam page could not be retrieved when this page was compiled - it returned a maintenance notice - so question count, time limit, and delivery format could not be confirmed from the source. Check the Oracle University exam page for 1Z0-117 before scheduling. Do not rely on figures from older blog posts, since exams are revised.
What score do I need to pass, and what does the exam cost?
Neither the passing score nor the registration fee could be sourced: the Oracle University page for 1Z0-117 was down for maintenance at retrieval. Both values change over time and by region. Confirm them on the official exam page or with your local Oracle University representative before you budget or book a seat.
How hard is the exam, and what trips people up?
It is a professional-level exam, so expect scenario questions that require choosing between similar OCI services rather than definitions. The most common failure mode is book-only study: candidates who have never created a project, published a conda environment, run a job, or deployed a model struggle to reason about which construct fits a constraint.
If I fail, can I retake it, and how soon?
The retake policy could not be confirmed because the official exam page was unavailable at retrieval. Oracle certification retake rules, waiting periods, and any fees are set by Oracle University and have changed in the past. Verify the current policy on the official certification page before assuming you can re-sit immediately.
How long is the certification valid?
Validity period could not be sourced from the official page, which was down for maintenance. Oracle has used different validity windows across its certification generations, and some credentials require periodic renewal. Check the current statement on Oracle University for 1Z0-117 rather than relying on memory or third-party summaries.
What study order do you recommend?
Start with the OCI Data Science service model - projects, notebook sessions, and environments - because everything else builds on it. Then move to jobs and the model catalog, then deployments, and finish with pipelines and MLOps. Do each step in a real tenancy as you read, so the console and SDK terminology is familiar before exam day.
Do I need coding skills for this exam?
Yes, practically speaking. OCI Data Science is Python-centric: notebook sessions, conda environments, job runs, and pipeline steps are all defined through the SDK and YAML or Python definitions. Candidates who only know the console tend to miss questions about environment publishing, job artifacts, and how pipeline steps pass outputs to each other.
How should I prepare in the final week?
Re-run your lab end to end without notes: create a project, publish an environment, submit a job, register a model, deploy it, and invoke the endpoint. Then review the official exam guide topics and write down the decision rule for each service boundary - notebook versus job, model catalog versus deployment, pipeline versus ad hoc run.