Machine Learning Concepts for Entrepreneurs and Managers Training Course

Course Code



21 hours (usually 3 days including breaks)


  1. Should have basic knowledge of business operation, and technical knowledge as well
  2. Must have basic understanding of software and systems
  3. Basic understanding of Statistics (in Excel levels)


Αυτό το εκπαιδευτικό μάθημα απευθύνεται σε άτομα που θα ήθελαν να εφαρμόσουν την Machine Learning σε πρακτικές εφαρμογές για την ομάδα τους. Η εκπαίδευση δεν θα εξελιχθεί σε τεχνικές λεπτομέρειες και θα περιστρέφεται γύρω από τις βασικές έννοιες και τις επιχειρησιακές / επιχειρησιακές εφαρμογές της ίδιας.

Στοχευμένο κοινό

  1. Επενδυτές και επιχειρηματίες της ΑΠ
  2. Διευθυντές και Μηχανικοί των οποίων η εταιρεία μπαίνει σε χώρο ΑΙ
  3. Αναλυτές Business & Επενδυτές

Machine Translated

Course Outline

Introduction to Neural Networks

Introduction to Applied Machine Learning

  • Statistical learning vs. Machine learning
  • Iteration and evaluation
  • Bias-Variance trade-off

Machine Learning with Python

  • Choice of libraries
  • Add-on tools

Machine learning Concepts and Applications


  • Linear regression
  • Generalizations and Nonlinearity
  • Use cases


  • Bayesian refresher
  • Naive Bayes
  • Logistic regression
  • K-Nearest neighbors
  • Use Cases

Cross-validation and Resampling

  • Cross-validation approaches
  • Bootstrap
  • Use Cases

Unsupervised Learning

  • K-means clustering
  • Examples
  • Challenges of unsupervised learning and beyond K-means

Short Introduction to NLP methods

  • word and sentence tokenization
  • text classification
  • sentiment analysis
  • spelling correction
  • information extraction
  • parsing
  • meaning extraction
  • question answering

Artificial Intelligence & Deep Learning

Technical Overview

  • R v/s Python
  • Caffe v/s Tensor Flow
  • Various Machine Learning Libraries

Industry Case Studies



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As a NobleProg Trainer you will be responsible for:

  • delivering training and consultancy Worldwide
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At the moment we are focusing on the following areas:

  • Statistic, Forecasting, Big Data Analysis, Data Mining, Evolution Alogrithm, Natural Language Processing, Machine Learning (recommender system, neural networks .etc...)
  • Hibernate/Spring, Scala, Spark, jBPM, Drools
  • R, Python
  • Mobile Development (iOS, Android)
  • LAMP, Drupal, Mediawiki, Symfony, MEAN, jQuery
  • You need to have patience and ability to explain to non-technical people

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