Vocational Courses

MS Word Basics: Introduction to Word interface, document creation, and basic formatting.
Intermediate MS Word: Working with styles, tables, and advanced formatting.
Advanced MS Word: Creating complex documents, using templates, and document automation.
MS Word for Business: Professional document creation, mail merges, and collaboration tools.
MS Word for Publishing: Layout design, creating brochures, and preparing documents for print.

MS Excel Basics: Introduction to spreadsheets, basic formulas, and data entry.
Intermediate MS Excel: Data management, functions, and creating charts.
Advanced MS Excel: Pivot tables, advanced formulas, macros, and VBA programming.
Excel for Data Analysis: Using Excel for statistical analysis, data visualization, and business intelligence.
Excel for Financial Modeling: Building and analyzing financial models with advanced techniques.

MS PowerPoint Basics: Creating and formatting presentations, using templates.
Intermediate MS PowerPoint: Enhancing presentations with graphics, charts, and multimedia.
Advanced MS PowerPoint: Custom animations, interactive presentations, and advanced design techniques.
PowerPoint for Business: Crafting impactful presentations for business meetings and reports.
PowerPoint Design Principles: Applying design principles for professional and engaging slides.

Tally Basics: Introduction to Tally software, basic accounting principles, and transactions.
Intermediate Tally: Managing inventory, generating reports, and handling GST.
Advanced Tally: Customizing Tally for specific business needs, advanced financial reporting.
Tally ERP 9: Comprehensive training on Tally ERP 9 features and functionalities.
Tally for Payroll Management: Managing payroll, employee records, and statutory compliance using Tally.

MATLAB Basics: Introduction to MATLAB environment, basic programming, and operations.
MATLAB for Data Analysis: Data manipulation, visualization, and statistical analysis.
MATLAB for Engineering: Applying MATLAB for simulations, engineering problem-solving, and modeling.
MATLAB Simulink: Introduction to Simulink for system modeling and simulation.
Advanced MATLAB: Advanced programming techniques, toolboxes, and custom functions.

Python Basics: Introduction to Python syntax, data types, and basic programming concepts.
Python for Data Science: Data analysis, manipulation, and visualization using Python libraries (pandas, NumPy, Matplotlib).
Python for Web Development: Building web applications using frameworks like Flask and Django.
Python for Machine Learning: Implementing machine learning models and algorithms with Python libraries (scikit-learn, TensorFlow).
Advanced Python: Advanced programming concepts, object-oriented programming, and performance optimization.

SAS Basics: Introduction to SAS programming, data manipulation, and basic procedures.
SAS for Data Analysis: Statistical analysis, data cleaning, and reporting with SAS.
SAS for Advanced Analysis: Advanced techniques for predictive modeling and statistical analysis.
SAS Macro Programming: Creating and using macros to automate repetitive tasks in SAS.
SAS Business Intelligence: Generating business reports, dashboards, and data visualization.

Introduction to AI: Basic concepts, applications, and history of AI.
AI Fundamentals: Core principles, machine learning algorithms, and neural networks.
AI for Business: Applying AI to solve business problems, including customer analytics and process automation.
AI Ethics and Policy: Understanding the ethical implications and governance of AI technologies.
Advanced AI Techniques: Deep learning, reinforcement learning, and AI optimization methods.

Machine Learning Basics: Introduction to machine learning concepts and algorithms.
Supervised Learning: Techniques for regression, classification, and model evaluation.
Unsupervised Learning: Clustering methods, dimensionality reduction, and anomaly detection.
Machine Learning with Python: Implementing algorithms and models using Python libraries (scikit-learn, TensorFlow).
Advanced Machine Learning: Deep learning architectures, neural networks, and advanced model tuning.

Introduction to Verilog: Basics of Verilog syntax, data types, and constructs.
Verilog for Digital Design: Designing and simulating digital circuits and systems.
Intermediate Verilog: Advanced constructs, testbenches, and state machines.
Verilog for FPGA: Implementing designs on FPGA using Verilog.
Advanced Verilog: Complex designs, verification methodologies, and optimization techniques.

Introduction to Quantum Computing: Basics of quantum mechanics and computing principles.
Getting Started with Qiskit: Introduction to the Qiskit framework and basic quantum programming.
Quantum Algorithms: Implementing fundamental quantum algorithms using Qiskit.
Quantum Circuit Design: Designing and analyzing quantum circuits and applications.
Advanced Qiskit: Advanced quantum computing concepts, quantum error correction, and optimization.

This structured 6-week training program is designed to provide polytechnic and engineering students with practical experience and insights into various industrial and institutional settings. The program aims to bridge the gap between academic knowledge and real-world applications, enhancing students’ employability and practical skills.

Duration: 6 Weeks.
Target Audience: Polytechnic and Engineering College Students.
Objective: To provide hands-on experience, industry insights, and practical skills relevant to the students’ field of study.

These courses can be tailored to different skill levels, from beginners to advanced users, and can be delivered through various formats such as online modules, in-person workshops, or blended learning environments.