FREE-iNTERNSHIP TRAINING
eLIGIBILITY : 6TH & 8TH sEMESTER ENGINEERING STUDENTS

Free-Internship Training Program by ISM UNIV

“Embedded System Development with ARDUINO UNO” – 45 Hours

📘 Program Description

This internship program provides hands-on training in developing embedded systems using the Arduino Uno microcontroller platform.
Students will learn the fundamentals of embedded systems, electronics, sensors, actuators, programming with Arduino IDE, interfacing modules, and real-time project development.

The program is designed with a practical, project-based approach, enabling participants to design, build, test, and deploy embedded applications.
By the end of the internship, students will create working hardware projects that can be showcased in their portfolio.

🎯 Learning Outcomes

Participants will be able to:

✓ Understand embedded systems architecture
✓ Program Arduino Uno using C/C++
✓ Interface sensors, actuators & external modules
✓ Work with digital & analog I/O
✓ Implement communication protocols (UART, I2C, SPI)
✓ Build real-world embedded projects
✓ Debug hardware and firmware problems
✓ Design and present a complete embedded project

⏱️ Duration: 45 Hours

📚 Detailed 45-Hour Training Content

MODULE 1: Introduction to Embedded Systems & Arduino (5 Hours)

1. Introduction to Embedded Systems (2 hrs)

• What is an embedded system?
• Architecture & components
• Microcontroller vs Microprocessor
• Real-time systems
• Applications in different industries

2. Introduction to Arduino Uno (3 hrs)

• Arduino board overview
• ATmega328P microcontroller architecture
• Pin configuration & functions
• Power supply requirements
• Installing Arduino IDE
• Basics of C programming for Arduino

MODULE 2: Arduino Programming Essentials (8 Hours)

1. Arduino IDE & Basic Programming (3 hrs)

• Structure of Arduino code (setup & loop)
• Data types, variables, operators
• Conditions & loops
• Functions, arrays
• Digital write/read
• Serial monitor basics

2. Working with Digital I/O (2 hrs)

• LED interfacing
• Push button & debounce
• Buzzer interfacing
• Practical exercises

3. Working with Analog I/O (3 hrs)

• ADC basics
• Reading analog sensors
• Potentiometer input
• PWM output
• Controlling LED brightness
• Servo motor basics

MODULE 3: Interfacing Sensors & Actuators (10 Hours)

1. Sensor Interfacing (5 hrs)

• Temperature sensor (LM35 / DHT11)
• IR sensor, LDR sensor
• Ultrasonic sensor
• Gas sensor (MQ series)
• Motion sensor (PIR)
• Hands-on testing & calibration

2. Actuator Interfacing (3 hrs)

• DC motor control
• Relay module
• LCD 16×2 display interface
• Stepper motor basics

3. Working with Communication Modules (2 hrs)

• Bluetooth Module (HC-05)
• WiFi Module Basics (ESP01) – Optional
• Sending/receiving commands through serial

MODULE 4: Communication Protocols & Advanced Concepts (7 Hours)

1. Communication Protocols (3 hrs)

• UART communication
• I2C protocol
• SPI protocol
• Interfacing I2C LCD
• Data logging basics

2. Timers & Interrupts (2 hrs)

• Hardware timers overview
• Interrupt service routines (ISRs)
• External hardware interrupts
• Real-time responsiveness

3. Power Management & Circuit Design (2 hrs)

• Voltage regulation
• Breadboard vs PCB
• Basics of circuit design
• Safety precautions

MODULE 5: Building Embedded Projects (10 Hours)

Students will apply the knowledge to develop complete working projects.

Sample Projects:

Students choose any one or trainer assigns based on level.

⭐ Beginner-Level

• Digital Thermometer
• Automatic Street Light Control
• IR-based Object Counter
• Clap Switch
• Distance measurement system
• Digital Dice Game

⭐ Intermediate-Level

• Smart Home Automation System
• Bluetooth Controlled Robot
• Obstacle Avoiding Robot
• Temperature & Humidity Monitoring System
• Smart Irrigation System
• RFID Door Lock System

⭐ Advanced-Level (Optional)

• IoT-based Data Monitoring
• Voice-Controlled Automation
• Mini Weather Station
• Solar Tracker System

Project Deliverables:

• Project circuit diagram
• Code documentation
• Hardware assembly
• Testing & debugging
• Final project demonstration & presentation

📄 Deliverables Provided to Students

✔ Internship Certificate
✔ Project Source Code
✔ Project Report (PDF)
✔ Hardware circuit diagrams & notes
✔ Resume-ready project content
✔ Lifetime access to training materials

Free-Internship Training Program by ISM UNIV

“Developing an AI Model using PYTHON” – 45 Hours

📌 Program Description

This internship program is designed to equip students with practical, hands-on experience in developing Artificial Intelligence (AI) models using Python.
Participants will learn the fundamentals of Python programming, essential AI and machine learning concepts, data preprocessing techniques, model building, training, evaluation, optimization, and deployment.

The training follows a project-based learning approach, where students work on real-world datasets and develop a complete AI model end-to-end.
By the end of the internship, students will have built a deployable AI model and gained skills required for entry-level roles in AI, Machine Learning, Data Science, and Automation.

🎯 Learning Outcomes

After completing this internship, participants will be able to:

✅ Understand Python essentials for AI development
✅ Work with data using NumPy, Pandas, and Matplotlib
✅ Apply Machine Learning concepts to solve real-world problems
✅ Build supervised and unsupervised ML models
✅ Train, evaluate, optimize, and tune AI models
✅ Implement model deployment using Flask / Streamlit
✅ Understand AI ethics, model biases & real project workflows
✅ Build and submit a complete AI project portfolio

⏱️ Duration: 45 Hours

Below is the recommended hour-wise structured curriculum.

📚 Detailed 45-Hour Course Content

MODULE 1: Python Essentials for AI (8 Hours)

1. Introduction to AI & ML (1 hr)

• What is AI, ML, DL?
• Real-world AI use cases
• Types of ML: Supervised, Unsupervised, Reinforcement

2. Python Basics Refresher (2 hrs)

• Variables, operators, conditions, loops
• Functions, modules, packages
• Working with files

3. Python for Data Handling (2 hrs)

• NumPy: arrays, operations, broadcasting
• Pandas: Series, DataFrames, data cleaning, manipulation

4. Data Visualization (3 hrs)

• Matplotlib & Seaborn basics
• Graphs: line, bar, histogram, scatter, heatmap
• Visualizing correlations and distributions

MODULE 2: Machine Learning Foundations (10 Hours)

1. Understanding ML Workflow (1 hr)

• Loading data
• Splitting datasets
• Training, testing, validation

2. Supervised Learning Algorithms (5 hrs)

• Linear Regression
• Logistic Regression
• Decision Trees & Random Forest
• Support Vector Machines
• Evaluation metrics: accuracy, precision, recall, F1-score

3. Unsupervised Learning Algorithms (3 hrs)

• Clustering (K-means, Hierarchical)
• Dimensionality Reduction (PCA)

4. Feature Engineering (1 hr)

• Encoding, normalization, scaling
• Handling missing values
• Feature selection & extraction

MODULE 3: Building the AI Model (12 Hours)

1. Project Data Collection & Understanding (2 hrs)

• Dataset selection
• Problem formulation
• Exploratory Data Analysis (EDA)

2. Model Development (4 hrs)

• Selecting algorithm
• Training the model
• Hyperparameter tuning (GridSearchCV / RandomizedSearchCV)

3. Model Evaluation (3 hrs)

• Confusion matrix
• ROC curve & AUC
• Cross-validation techniques

4. Model Optimization (3 hrs)

• Bias-variance tradeoff
• Overfitting vs underfitting
• Regularization techniques

MODULE 4: AI Model Deployment (8 Hours)

1. Introduction to Deployment (1 hr)

• Importance of deployment
• Local vs cloud deployment

2. Deploying with Flask (3 hrs)

• Creating Flask API
• Sending model predictions via API
• Testing with Postman

OR
Deploying with Streamlit (3 hrs)

• Building an interactive dashboard
• Input forms, prediction display
• Hosting options (Streamlit Cloud)

3. Saving and Loading Models (1 hr)

• Pickle
• Joblib

4. End-to-End Integration (3 hrs)

• Integrating model with UI
• Creating a final working application

MODULE 5: Internship Project (7 Hours)

Students will work on one real AI project such as:

Project Options (Choose Any):

• House Price Prediction
• Customer Churn Prediction
• Loan Eligibility Prediction
• Diabetes Detection Model
• Spam Email Classifier
• Movie Recommendation System
• Sales Forecasting Model
• Image Classification (basic CNN using TensorFlow – optional)

Project Deliverables:

• Problem definition
• Dataset preprocessing
• Model building and tuning
• Evaluation report
• Deployment (Flask/Streamlit app)
• Final project presentation

📄 Deliverables Provided to Students

✔ Internship Certificate
✔ AI Project Source Code
✔ Project Report (PDF)
✔ Resume Projects (1–2)
✔ Training Materials & Notes
✔ Lifetime Access to Model Notebook

Free-Internship Training Program by ISM UNIV

“Data Analytics using Power BI” – 45 Hours

📘Program Description

This internship program provides hands-on training in Data Analytics using Microsoft Power BI, one of the most in-demand business intelligence tools used by organizations worldwide.
Participants will learn how to connect, clean, transform, analyze, and visualize data to deliver actionable business insights.

The internship follows a practical, project-driven approach, where students work with real datasets to build interactive dashboards, data models, and analytical reports.
By the end of the program, learners will be able to develop end-to-end BI solutions suitable for professional roles such as Business Analyst, Data Analyst, BI Developer, and Reporting Analyst.

🎯 Learning Outcomes

After completing this internship, participants will be able to:

✓ Understand core concepts of data analytics & BI
✓ Perform data cleaning, transformation & modeling using Power Query
✓ Create interactive dashboards with advanced visualizations
✓ Write DAX calculations for measures & KPIs
✓ Build relationships and optimize data models
✓ Publish, share, and manage reports in Power BI Service
✓ Apply analytics to solve real industry problems
✓ Build and present a real-world data analytics project

⏱ Duration: 45 Hours

📚 Detailed 45-Hour Training Content

MODULE 1: Foundations of Data Analytics & Power BI (5 Hours)

1. Introduction to Data Analytics (1 hr)

• Types of analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
• Role of a Data Analyst
• BI ecosystem & tools

2. Getting Started with Power BI (2 hrs)

• Power BI Desktop vs Power BI Service
• Interface overview
• Connecting different data sources

3. Understanding Business Reporting (2 hrs)

• What makes a good dashboard?
• KPI concepts
• Dashboard design principles

MODULE 2: Power Query – Data Cleaning & Transformation (10 Hours)

1. Introduction to Power Query (3 hrs)

• ETL Concepts
• Query Editor Interface
• Importing large datasets

2. Data Cleaning Techniques (4 hrs)

• Removing duplicates & errors
• Handling missing values
• Column splitting, merging
• Data type conversions
• Filtering, sorting, grouping

3. Data Transformation (3 hrs)

• Pivot & unpivot
• Conditional columns
• Derived columns
• Appending & merging queries

MODULE 3: Data Modeling & DAX (10 Hours)

1. Data Modeling Concepts (3 hrs)

• Star & Snowflake schema
• Fact & Dimension tables
• Creating relationships
• Cardinality & cross-filtering

2. DAX Fundamentals (4 hrs)

• Calculated columns vs Measures
• Basic DAX functions: SUM, COUNT, CALCULATE
• Time intelligence functions

3. Advanced DAX (3 hrs)

• Variables in DAX
• Filtering functions (FILTER, ALL)
• Evaluation context
• KPI creation

MODULE 4: Data Visualization & Dashboard Design (10 Hours)

1. Power BI Visuals (4 hrs)

• Bar, line, pie charts
• Cards, tables, matrices
• Maps & geospatial visuals
• Tree map, funnel, scatter plot

2. Advanced Visualizations (3 hrs)

• Custom visuals
• Bookmarks & storytelling
• Tooltips & drill-through
• Slicers & filters

3. Dashboard Best Practices (3 hrs)

• Choosing the right chart
• Layout & design rules
• Color themes
• User navigation techniques

MODULE 5: Power BI Service & Deployment (5 Hours)

1. Publishing Reports (2 hrs)

• Uploading reports to Power BI Service
• Datasets, Workspaces, Apps
• Data refresh schedules

2. Sharing & Collaboration (2 hrs)

• Sharing dashboards
• Managing permissions
• Exporting reports

3. Mobile Layout (1 hr)

• Designing mobile-friendly dashboards
• Testing on Power BI Mobile

MODULE 6: Internship Project (5 Hours)

Students will build a complete analytical dashboard using real-world data.

Sample Project Options:

• Sales Analytics Dashboard
• HR Attrition Dashboard
• Financial Performance Dashboard
• Retail Store Performance Dashboard
• Student Performance Analytics
• Hospital/Healthcare Analytics
• Supply Chain Dashboard
• Marketing Campaign Performance Dashboard

Project Deliverables:

• Power Query cleaning & transformation
• Data modeling
• DAX calculations
• Interactive dashboard
• Project documentation & presentation

📄 Deliverables Provided to Students

✔ Internship Certificate
✔ Project Power BI File (.pbix)
✔ Dashboard Screenshots for Resume
✔ Project Report (PDF)
✔ Notes & Dataset
✔ Resume-ready Data Analytics Project