Our Training Programs

Learn from industry practitioners

Hands-on, enterprise-grade training in Oracle PL/SQL, Data Science & AI, and Oracle Database Administration. Click any course to view the full outline.

Oracle PL/SQL Training

Procedural Language for SQL · 8 modules

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Module 1 — Programming Fundamentals & PL/SQL Introduction

Overview of Programming Languages
Introduction to Oracle PL/SQL & its architecture
Key benefits, features and PL/SQL data types
Variables, constants and built-in functions
Conditional & unconditional statements: IF, IF-ELSE, Nested IF-ELSE, IF-ELSE ladder
CASE statements, GOTO, labels and EXIT statements

Module 2 — Iterative Processing & SQL Integration

Looping techniques: Simple LOOP, WHILE, FOR and nested loops
Executing SQL statements within PL/SQL blocks
Composite data types and collections

Module 3 — Cursor Management

Implicit & explicit cursors and cursor attributes
Parameterized cursors, cursors with loops and nested cursors
Cursors with subqueries and REF cursors
Records and PL/SQL table types

Module 4 — Advanced PL/SQL Programming

Creating and managing stored procedures
IN, OUT and IN OUT parameters
Positional and named notation; procedures using cursors
Modifying and dropping procedures

Module 5 — Functions in PL/SQL

User-defined functions and nested functions
Differences between procedures and functions
Using stored functions in SQL statements

Module 6 — Packages

Package specifications and bodies
Public and private package objects
Best practices for package development

Module 7 — Exception Handling

Predefined and user-defined exceptions
RAISE_APPLICATION_ERROR and PRAGMA AUTONOMOUS_TRANSACTION
Understanding SQL error codes and messages

Module 8 — Database Triggers

Types of triggers; row-level and statement-level triggers
DDL triggers and trigger-based auditing techniques

Course Outcome

By the end of this training, participants will be able to design, develop, debug and optimize PL/SQL programs, manage database objects efficiently, and build enterprise-grade database applications.

Data Science & AI Certification

Advanced Certification in Data Science and AI · 15 modules

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Module 1 — Preparatory Sessions: Python & Linux

Python: introduction to IDEs, basics, OOP and hands-on practice
Linux: introduction, basics and hands-on assignments

Module 2 — Data Wrangling with SQL

SQL basics & advanced SQL
User-defined functions
SQL optimization and performance

Module 3 — Python with Data Science

Data handling with NumPy
Data manipulation using Pandas
Data preprocessing and visualization

Module 4 — Linear Algebra & Advanced Statistics

Descriptive statistics and probability
Inferential statistics
Linear algebra

Module 5 — Machine Learning

Introduction to Machine Learning
Regression, classification and clustering

Module 6 — Supervised Learning

Linear & logistic regression, decision tree, random forest
SVM, K-Nearest Neighbors, time series forecasting
Performance metrics, classification reports, confusion & evaluation matrix

Module 7 — Unsupervised Learning

K-means and dimensionality reduction
Linear Discriminant Analysis & Principal Component Analysis

Module 8 — Deep Learning Using TensorFlow

Artificial Intelligence and neural network basics
Deep learning

Module 9 — Data Science Capstone Project

ETL and data pre-processing to gather insights
Feature engineering and scaling
Model selection, building and evaluation across supervised/unsupervised algorithms

Module 10 — Business Case Studies

Recommendation engine, rating predictions, census, housing
Object detection, stock market analysis, banking problem, AI chatbot

Module 11 — Generative AI

LSTM, Transformers, BERT, GPT and LLMs

Module 12 — Elective: Power BI

Power BI basics, DAX and data visualization with analytics

Module 13 — Deploying ML Models with Cloud

Introduction to MLOps and deploying machine learning models

Module 14 — GIT

Version control and Git

Module 15 — Data Analysis with MS-Excel

Excel fundamentals and Excel for data analytics
Data visualization, Excel power tools and classification problems
Information measure, regression problems and hands-on exercises

Oracle Database Administration

Comprehensive curriculum · 27 topics incl. ASM & advanced RMAN

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1–5 — Architecture, Installation & Instance Management

Oracle Database and ASM architecture; process and memory structures
Installing Oracle software with OUI and Grid Infrastructure (incl. silent installs)
Creating databases with DBCA; templates and security
Managing the Oracle instance; startup/shutdown stages, alert logs, ASM
Configuring the Oracle network environment and the Listener

6–11 — Storage, Security & Performance

Managing storage structures, tablespaces and Oracle Managed Files (OMF)
Administering user security, roles and profiles
Managing data concurrency, locks and deadlocks
Managing undo data and retention
Database auditing and audit trail maintenance
Performance management: AWR, ADDM, AMM and tuning views

12–16 — Backup, Recovery & Data Movement

Backup & recovery concepts; instance recovery and MTTR Advisor
Performing backups with RMAN and the Flash Recovery Area
Database recovery and the Data Recovery Advisor
Data movement: SQL*Loader, external tables and Oracle Data Pump
Working with Oracle Support and managing patches

17–23 — Advanced RMAN

RMAN recovery catalog, stored scripts and virtual private catalog
Configuring backup specifications, channels and optimization
Image copies, incremental, compressed and encrypted backups
User-managed backup and recovery scenarios
RMAN recovery operations, restoring to a new host
RMAN database duplication and cloning
Monitoring and tuning RMAN performance

24–27 — ASM & Advanced Topics

Automatic Storage Management fundamentals and disk groups
Failure groups, redundancy and disk group management
Creating and managing databases on ASM
Advanced RMAN: strategies, troubleshooting and best practices