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Robotics AI & ML IoT IT Foundations
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Course Tracks

Robotics

Robotics

From zero to building autonomous robots with sensors, control, and onboard AI.

  • Duration: 5 months
  • Level: Beginner → Advanced
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AI Programming

AI Programming

Python-first AI, data pipelines, and deploying models to real users.

  • Duration: 6 months
  • Level: Beginner → Intermediate
View Syllabus
Machine Learning

Machine Learning

Hands-on algorithms, feature engineering, and MLOps fundamentals.

  • Duration: 6 months
  • Level: Intermediate
View Syllabus
IoT

Internet of Things

Connect sensors, send data to the cloud, and automate with edge computing.

  • Duration: 4 months
  • Level: Beginner → Intermediate
View Syllabus
IT Foundations

IT Foundations

Computer essentials, networking, Linux, and Git to prepare you for tech.

  • Duration: 8 weeks
  • Level: Beginner
View Syllabus

What You Will Learn

Robotics

Module 1: Foundations
  • Safety, tools, and components
  • Electronics basics, sensors, actuators
  • Microcontrollers: Arduino, Raspberry Pi
  • Programming: Python, C/C++ basics
Module 2: Motion & Control
  • Kinematics and PID control
  • Motor drivers and encoders
  • Line following and obstacle avoidance
Module 3: Perception
  • Sensor fusion with IMU, ultrasonic, IR, camera
  • Basic computer vision
  • ROS introduction
Module 4: Autonomous Robot Project
  • Design, build, document
  • Demo day and portfolio

AI Programming

Module 1: Python for AI
  • NumPy, pandas, matplotlib
  • Data cleaning and EDA
Module 2: Classic ML
  • Supervised and unsupervised learning
  • Model evaluation and validation
Module 3: Neural Basics
  • Feedforward, CNNs, RNNs
  • Training, tuning, and regularization
Module 4: Deployment
  • APIs, containers, and simple UIs
  • Capstone: AI app

Machine Learning

Module 1: Math & Data
  • Linear algebra and probability refresh
  • Feature engineering and pipelines
Module 2: Advanced Models
  • Tree ensembles and boosting
  • SVMs and clustering
Module 3: Deep Learning
  • Modern architectures overview
  • Transfer learning
Module 4: MLOps
  • Experiment tracking
  • Model serving and monitoring

Internet of Things

Module 1: Hardware & Firmware
  • ESP32 and microcontrollers
  • Sensor drivers and power
Module 2: Connectivity
  • MQTT, HTTP, and WebSockets
  • Edge computing
Module 3: Cloud & Dashboards
  • Cloud ingestion and storage
  • Dashboards and alerts
Module 4: IoT Project
  • Prototype and demo
  • Security and scaling basics

IT Foundations

Module 1: Computer Essentials
  • OS basics and productivity
  • Security hygiene
Module 2: Networking
  • TCP/IP and wireless
  • Home lab setup
Module 3: Linux & Git
  • CLI workflows
  • Git branching
Module 4: Career Prep
  • Portfolio and interviews
  • Next steps into BI advanced tracks

Projects

Main Project Image

RMET v1

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Outcomes

What Our Students Say

Binary International opened the door to robotics for me. I built my first autonomous rover and got an internship.

– Aisha

The AI track was practical and clear. I shipped my first model-backed web app.

– Omar

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