TRAINING
Curriculum of Robotics/AI:
Students are considered to have completed our program (course) if they complete five (sequential) classes of the program.
These students will receive a Robotics Certificate from CBD Robotics. Classes will be highly specialized and focus on practical projects,
students must complete new projects that are approved upon completing the course. Each class lasts 4 months or 16 weeks.
Each week, students will attend 2 sessions. Each session lasts 2 hours,
This includes theory and guidance for building practical projects. Students will develop practical projects under guidance
of lecturers.
Python programming
| Unit 1 | Unit 2 | |
| Data types, control flow, functions, objects & classes | Postgresql database, data modeling, sqlalchemy and model relationships in Python | |
| Unit 3 | Unit 4 | |
| Flask and the basics, building blog, authentication using flask-login, Unit test | Api and web services, sending data API with POST, uploading files via API | |
| Unit 5 | ||
| Capstone project | ||
| Machine Learning in Python | ||
| Unit 1 | Unit 2 | |
| Sqlite database, Pandas, Statistics, Probability, Hypothesis testing, Probability Distributions | Acquiring data using json format, acquiring data from an API, scraping data from HTML websites | |
| Unit 3 | Unit 4 | |
| Linear Regression, Logistic Regression, Multivariate Regression, Time Series Regression | Classification, Fitting and Overfitting, Cross Validation, Random Forest, Bayes, KNN, Clustering, SVM, LDA, PCA | |
| Unit 5 | ||
| Capstone project | ||
| Natural Language Processing | ||
| Unit 1 | Unit 2 | |
| Language processing and Python, Accessing Corpora and Lexical resources | Processing Raw text, Categorizing and Tagging words | |
| Unit 3 | Unit 4 | |
| Classifying text, extracting information from text | Analyzing Sentence Structure, Analyzing the meaning of sentences | |
| Unit 5 | ||
| Capstone project | ||
| Deep Learning | ||
| Unit 1 | Unit 2 | |
| Tensorflow and the basics, MNIST | Neural network, hidden layer, convolutional layer, maxpooling layer, sub-sampling layer | |
| Unit 3 | Unit 4 | |
| Convolutional Neural Network for Image Processing | Recurrent Neural Networks for language processing | |
| Unit 5 | ||
| Capstone project | ||
| Computer Vision/Robotics | ||
| Unit 1 | Unit 2 | |
| Machine Learning for Machine Vision, binary classification, Expectation Maximization | Gaussian Mixtures, Factor Analysis, Face Recognition | |
| Unit 3 | Unit 4 | |
| Image Processing and feature extraction, the pinhole camera, multiple cameras | Models for style and identity, Temporal Models, Kalman Filter, Moving Objects | |
| Unit 5 | ||
| Capstone project |
You can watch video of AI products in the world via link: Demo of AI products