Oracle Machine Learning for Python

Oracle Machine Learning for Python

Duration : 2 Days (16 Hours)

Oracle Machine Learning for Python Course Overview:

The Oracle Machine Learning for Python certification validates an individual’s ability to implement machine learning solutions using the Python language on Oracle platforms. It covers essential concepts such as data wrangling, exploratory data analysis, understanding algorithms, model selection, and deployment.

Industries rely on this certification as a benchmark to identify skilled professionals who can effectively use Python for machine learning in Oracle environments. It finds application in various sectors, including finance, healthcare, retail, and more, for predictive analytics, data modeling, algorithm development, and data-driven decision-making processes.

This certification serves as evidence of expertise in integrating Python’s capabilities with Oracle’s robust data management features, enabling professionals to harness the full potential of machine learning in Oracle ecosystems.

Intended Audience:

• Data scientists interested in learning Oracle Machine Learning
• Python programmers seeking to enhance their skills
• IT professionals working on machine learning projects
• Job aspirants aiming for a career in data science
• AI engineers looking to expand their knowledge in Oracle-focused machine learning
• Students studying computer science, machine learning, or related fields.

Learning Objectives of Oracle Machine Learning for Python:

The primary learning objectives for the Oracle Machine Learning for Python course are:

  1. Understanding the fundamentals of machine learning, its practical applications, and its role in data analysis.
  2. Learning to use Oracle Machine Learning algorithms within Python and apply them to real-time projects.
  3. Gaining proficiency in deploying machine learning algorithms on the Oracle platform.
  4. Manipulating and analyzing data using Python’s powerful data science libraries and tools.
  5. Utilizing Python with Oracle databases for more efficient data processing and analysis.

Module 1: Introduction to Machine Learning for Python

  • Introduction to Machine Learning for Python
  • Why Machine Learning and Use cases
  • Machine Learning Workflow and Types of ML Algorithms
  • Introduction to Oracle Machine Learning for Python and Features
  • OML4Py Features
  • Oracle Machine Learning for Python Advantages
  • OML Notebooks
  • Python Libraries in OML4Py

Module 2: OML4Py Transparency Layer

  • OML4Py Transparency Layer
  • Combine Data
  • Clean and Split Data
  • Data Exploration

Module 3: Working with Machine Learning Models

  • Working with Machine Learning Models
  • Common in-database algorithm features
  • Working with Machine Learning Models-I
  • Working with Machine Learning Models-II
  • Working with Machine Learning Models-III
  • Create a model proxy object from an existing model
  • Export and Import a Model

Module 4: Data Store for Python Objects

  • Data Store for Python Objects
  • Save Objects & Load Saved Objects from a Data Store
  • Get Information from a Data Store
  • Get Information and Delete Data Store Object
  • Manage access to stored objects

Module 5: OML4Py Automated Machine Learning

  • OML4Py Automated Machine Learning
  • Machine Learning Workflow Automated by AutoML
  • Algorithm Selection
  • Feature Selection
  • Model Tuning
  • Model Selection

Module 6: Embedded Python Execution

  • Introduction to Embedded Python Execution
  • Run a Python Function
  • Run a Python Function on the Specified Data
  • Run a Python Function on Data Grouped by Column Values
  • Introduction to Script Repository Overview
  • Load and Drop Script from Repository
  • Introduction to REST API

Module 7: Working with cx_Oracle

  • Working with cx_Oracle
  • Oracle Architecture
  • ReadWrite Table Methods

Oracle Machine Learning for Python Course Prerequisites:

• Basic understanding of Python programming language
• Basic knowledge in Oracle SQL and PL/SQL
• Familiarity with Oracle Database 12c or 18c
• Previous experience in Data Science, Machine Learning, or relevant field
• Experience in using Python libraries like Pandas, NumPy, and Matplotlib.

Discover the perfect fit for your learning journey

Choose Learning Modality

Live Online

  • Convenience
  • Cost-effective
  • Self-paced learning
  • Scalability

Classroom

  • Interaction and collaboration
  • Networking opportunities
  • Real-time feedback
  • Personal attention

Onsite

  • Familiar environment
  • Confidentiality
  • Team building
  • Immediate application

Training Exclusives

This course comes with following benefits:

  • Practice Labs.
  • Get Trained by Certified Trainers.
  • Access to the recordings of your class sessions for 90 days.
  • Digital courseware
  • Experience 24*7 learner support.

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