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IT Trainings List

Playwright with JAVA Script

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Cyber Security

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Python Full Stack

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Module 1: ServiceNow Platform Essentials (10 Days) Objective: Understand the core ServiceNow platform structure and basic configurations. Introduction to ServiceNow (Navigation, Application Explorer) Tables, Forms, Lists, and Dictionary Users, Roles, and Access Control (ACL basics) UI Policies, Data Policies, Client Scripts Business Rules & Script Includes Notifications and Email Configuration ServiceNow Studio & Scoped Applications Application Files: Modules, Menus, Roles Update Sets - Create, Export, Import Review + Quiz/Assessment Module 2: Core ITSM Applications (20 Days) Objective: Learn the full lifecycle and configuration of core ITSM processes: Incident, Problem, Change, and Request. Introduction to ITIL & ITSM in ServiceNow Incident Management: Overview, States, Priorities Incident Form, Assignment Rules, SLAs Auto-routing via Business Rules & Script Problem Management: Lifecycle, Root Cause Problem Form Customization Change Management: Normal, Standard, Emergency Change Approval Policies & Workflows Request Management vs Incident vs Change Catalog Items, Record Producers Catalog Item Variables & Variable Sets Request Workflow Design using Visual Workflow Editor Knowledge Management Basics SLAs: Definitions, Conditions, Retroactive Start Escalation Rules, Time Breach Alerts CAB Workbench Overview ITSM Reporting - Reports, Performance Analytics Intro Dashboards and Homepages Live Agent Chat, Virtual Agent Basics (optional) ITSM Use Case Lab (Automate Ticket Lifecycle) Module 3: Scripted Integrations (20 Days) Objective: Perform real-world ServiceNow integrations using Scripted REST, REST Message, and Inbound APIs. No IntegrationHub. Introduction to Integrations in ServiceNow REST API Concepts (Methods, Headers, JSON) Using REST API Explorer Scripted REST API - Create a custom API Scripted REST with Input Validation & Responses Consume External API with REST Message REST Message Authentication (Basic Auth / OAuth profile) Call External Weather/Currency APIs using Script Transform JSON/XML Data Test REST APIs using Postman Scheduled Scripted API Call (REST polling) Inbound REST: External system creates Incident Use Business Rule to Trigger Outbound REST REST Call Error Handling & Logging Mid Project Review: End-to-End Integration Import/Export JSON or CSV using Import Sets Script to Trigger Notifications from External Events Attachment API - Upload/Download Files via API Integration Best Practices & Security (ACLs, Rate Limits) Integration Lab: External Tool Creates Incident, Notifies on Closure Module 4: Final Project & Certification Prep (10 Days) Objective: Implement a full use case and prepare for interviews and CSA certification. Use Case Finalization & Planning Final Project: Scripted Integration for Ticketing Presentation & Documentation CSA Certification Overview & Practice Questions Mock Test (CSA-style) Career Guidance + Interview Q&A + Feedback Tools & Deliverables Tools: - ServiceNow PDI - Postman - VS Code (optional) - GitHub (optional) Deliverables: - Lab Exercises - API Scripts - ITSM Customization Scripts - Final Integration Project - CSA Mock Exam Pack - Resume + Projects

ServiceNow

ServiceNow

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JAVA

Java Developer Program

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Course Syllabus Overview Excel for Data Analysis Build a solid foundation in data handling and reporting: Excel interface, shortcuts & formatting Formulas, functions, and conditional formatting Data cleaning (TRIM, CLEAN, remove duplicates) Sorting, filtering, data validation, and pivot tables Hands-on data analysis exercises SQL for Data Management Learn to query, manage, and analyze data effectively: SQL fundamentals, DBMS & RDBMS concepts SELECT, WHERE, DISTINCT, ORDER BY, and filtering Aggregate functions (COUNT, SUM, AVG, MIN, MAX) Joins: Inner, Left, Right, Full, Self, Cross Subqueries, Views, Stored Procedures, Indexes Transactions, Exception Handling, and Case Studies Python for Data Science Master Python programming and its applications in analytics: Python setup, Jupyter Notebook, Git & GitHub Variables, operators, conditionals, loops & functions Data structures – List, Tuple, Set, Dictionary File handling (CSV, JSON, TXT) and custom modules NumPy for numerical computing and linear algebra Pandas for data manipulation, grouping, and merging Data cleaning, feature engineering & outlier treatment Data Visualization & Statistics Transform raw data into insights: Charts with Matplotlib and Seaborn (bar, line, heatmap) Interactive visuals using Plotly Descriptive statistics, probability distributions Hypothesis testing, correlation, and sampling Machine Learning Explore predictive modeling and pattern recognition: Supervised learning – Linear/Logistic Regression, Decision Trees, Random Forests, SVM, KNN Unsupervised learning – Clustering, Association Rules, Recommender Systems Model evaluation, feature selection & optimization Artificial Intelligence & Deep Learning Learn modern AI concepts and neural networks: Introduction to AI, ML, and Deep Learning Neural networks, activation & loss functions TensorFlow & PyTorch fundamentals CNNs for image recognition, RNNs for time series LSTM, GRU, and Transfer Learning (VGG, ResNet) NLP – Sentiment Analysis, NER, Text Generation Generative Models – Autoencoders, GANs Transformers, BERT, GPT & Explainable AI (XAI) Model Deployment & Cloud Integration Bring your models to life: Model deployment with Flask, FastAPI, Streamlit Cloud AI pipelines: AWS SageMaker, Azure AI, Google Vertex AI Monitoring, maintenance, and scaling models Big Data & Cloud Analytics Master large-scale data handling: Hadoop: Architecture & ecosystem PySpark: Distributed computing Hive: Querying Big Data efficiently AWS: Cloud model deployment & integration Agile & Scrum Methodology Learn Agile project management and Scrum frameworks for delivering data projects in corporate environments. Program Highlights Instructor-Led Online & Offline Classes Real-Time Projects & Internships Case Studies & Cloud Deployments Doubt-Clearing Sessions & Mentorship Career Support & Job Assistance Career Outcomes Become job-ready for roles like: Data Scientist Machine Learning Engineer AI Engineer Data Analyst Business Intelligence Developer

Data Science, AI & ML

Data Science, AI & ML Training Program

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Program Structure     1. GenAI & LLM Fundamentals Introduction to Generative AI & Large Language Models (LLMs) ChatGPT, Claude, Gemini, DeepSeek, Sora, and Midjourney Prompt Engineering & No-Code AI Tools   2. RAG Implementation End-to-End RAG Architecture Vector Databases, Embeddings, and Search Indexing Cloud Deployment on Google Vertex AI, AWS Bedrock, and Azure OpenAI   3. Fine-Tuning & Agentic Frameworks LoRA, QLoRA, and Model Optimization LangChain, LangGraph, CrewAI, and MCP Integrations AI Agents: Concepts, Architecture, and Use Cases   4. Project Development Build Your Own AI Chat System Implement RAG-Based Knowledge Apps Cloud Deployment & Model Evaluation   Key Highlights Learn from Real-Time GenAI Experts Hands-On LLM Projects & Tools “Ask Questions to Test & Train Your AI Chat” Interactive Labs Job Assistance & Industry Mentorship   Who Should Join Ideal for IT professionals, AI enthusiasts, and developers looking to master Generative AI, LLMs, and AI Automation Frameworks for real-world applications.

Generative AI

Generative AI
Training Program

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