Vendor: Cloud Contraptions
Format: Live instructor-led
Duration: 14 hours of live training delivered over 2-4 days to accommodate your scheduling needs
- Course details available on vendor site
- PostgreSQL
- Overview of PostgreSQL
- Key Features and Benefits
- Use Cases in the Industry
- Setting Up PostgreSQL
- Installing PostgreSQL on Different Operating Systems
- Basic Configuration and Post-Installation Setup
- PostgreSQL Architecture
- System Architecture and Process Model
- Data Storage and Tablespaces
- Basic SQL with PostgreSQL
- Basic SQL Syntax and Data Types
- Creating, Altering, and Dropping Tables
- CRUD Operations (Create, Read, Update, Delete)
- Advanced SQL Techniques
- Complex Queries: Joins, Subqueries, and Common Table Expressions (CTEs)
- Functions and Operators: Built-in and User-Defined
- Aggregate Functions and Grouping
- Database Design and Modeling
- Normalization and Denormalization
- Entity-Relationship Modeling and Schema Design
- Performance Tuning and Optimization
- Using EXPLAIN and ANALYZE for Query Optimization
- Indexing Strategies and Index Maintenance
- Performance Tips and Configuration Tuning
- Concurrency and Transactions
- Transactions, ACID Properties, and Isolation Levels
- Locking Mechanisms and Concurrency Control
- Multi-Version Concurrency Control (MVCC)
- Security and Authentication
- User Management and Role-Based Access Control
- Authentication Methods and Configuring pg_hba.conf
- Data Encryption Techniques and SSL/TLS Configuration
- Python Programming with PostgreSQL
- Setting Up Psycopg2
- Connecting to PostgreSQL from Python
- Performing CRUD Operations with Python
- Using SQLAlchemy with PostgreSQL
- Handling Transactions in Python
- Working with JSON Data
- Working with Vectors
- Loading Data from PostgreSQL into Pandas
- Writing SQL Queries to Retrieve Data
- Using pandas.read_sql() to Load Data
- Handling Large Datasets Efficiently
- Writing Data from Pandas to PostgreSQL
- Creating New Tables from DataFrames
- Inserting and Updating Data in Existing Tables
- Using pandas.to_sql() for Efficient Data Transfers
- Handling Data Types and Indexes
- Mapping Data Types Between Pandas and PostgreSQL
- Ensuring Data Integrity and Consistency
- Managing Indexes for Optimized Performance
- Extending PostgreSQL
- Using Procedural Languages: PL/pgSQL, PL/Python, PL/Perl
- Working with Extensions and Modules
- Popular Extensions (PostGIS, hstore, etc.)
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- We specialize in delivering computer programming training and consulting services with an emphasis on using the latest in AI technology. We are customer-friendly and employ AI best practices and teach these practices to companies around the world.
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- Contact Info
- +1 434-945-9416
- help@cloudcontraptions.com
- 3378 South Amherst Hwy
- Unit 21
- Monroe, VA 24574
- © 2026 Cloud Contraptions LLC. All Rights Reserved.
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- Designed for software and data engineers, Python developers, analytics engineers, and DB-adjacent SREs working on production systems. Technical leads and engineering managers evaluating database choices will also benefit. Attendees should be comfortable with programming fundamentals and seek to improve query performance, data modeling, security posture, and Python–PostgreSQL data pipelines to accelerate delivery and impact business KPIs.
- Experience with Python programming is required
- No prior experience with PostgreSQL is necessary
- Students should have a basic understanding of SQL and relational databases
Source Host: www.cloudcontraptions.com
Generated on 2026-04-16 03:37:14