Classroom course

Python for data science

classroom course

Python for data science

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    Price
    533 € + VAT
    Duration
    16 hours
    Date:
    June 13th-14th
    Qualification obtained
    Certificate
    Course code
    AGSAI003
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      Python is a programming language used in multiple scientific contexts and corporate. Python supports several paradigms of programming, such as the object-oriented paradigm, imperative and functional and turns out to be ideal for making Machine Learning applications.

      Who is it for?

      The course is aimed at:

      Anyone who already knows the basics of python and wants to deepen its use in machine learning.

      Objective
      In the advanced course the most acquainted libraries and the implementation of some of the most important algorithms will be presented.
      Program
      PHYTON PER DATA SCIENCE

      Introduction to using python for Data Science.

      • 1. Numpy
      • 2. Pandas
        • 2.1 Series, DataFrame
        • 2.2 Operations on DataFrames
      • 3. Matplolib
        • 3.1 Plotting fundamentals
        • 3.2 Dispersion charts
        • 3.3 Line charts
        • 3.4 Bar charts
        • 3.5 Histograms
        • 3.6 Box plot
        • 3.7 Heatmaps
      • 4. Seaborn
      • 5. Introduction to ML (theory)
      • 6. Scikit-learn
        • 6.1 K-nearest neighbors
        • 6.2 Linear regression
        • 6.3 Logistic regression
        • 6.4 SVM
        • 6.5 Naive Bayes
        • 6.6 Decision trees
        • 6,7 Random Forests (ensemble learning, boosting, bagging)
        • 6.8 Clustering
      • 7. Valutazione dei modelli
        • 7.1 Matrice di confusione
        • 7.2 Curva ROC, precision e recall
      Classroom and safety rules
      To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.

      Python is a programming language used in multiple scientific contexts and corporate. Python supports several paradigms of programming, such as the object-oriented paradigm, imperative and functional and turns out to be ideal for making Machine Learning applications.

      Who is it for?

      The course is aimed at:

      Anyone who already knows the basics of python and wants to deepen its use in machine learning.

      Objective
      In the advanced course the most acquainted libraries and the implementation of some of the most important algorithms will be presented.
      Program
      PHYTON PER DATA SCIENCE

      Introduction to using python for Data Science.

      • 1. Numpy
      • 2. Pandas
        • 2.1 Series, DataFrame
        • 2.2 Operations on DataFrames
      • 3. Matplolib
        • 3.1 Plotting fundamentals
        • 3.2 Dispersion charts
        • 3.3 Line charts
        • 3.4 Bar charts
        • 3.5 Histograms
        • 3.6 Box plot
        • 3.7 Heatmaps
      • 4. Seaborn
      • 5. Introduction to ML (theory)
      • 6. Scikit-learn
        • 6.1 K-nearest neighbors
        • 6.2 Linear regression
        • 6.3 Logistic regression
        • 6.4 SVM
        • 6.5 Naive Bayes
        • 6.6 Decision trees
        • 6,7 Random Forests (ensemble learning, boosting, bagging)
        • 6.8 Clustering
      • 7. Valutazione dei modelli
        • 7.1 Matrice di confusione
        • 7.2 Curva ROC, precision e recall
      Classroom and safety rules
      To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.
      REQUEST INFORMATION




        * Required field

        Price
        533 € + VAT
        Duration
        16 hours
        Date:
        June 13th-14th
        Qualification obtained
        Certificate
        Course code
        AGSAI003
        subscribe

          Participant's personal data:







          Billing data (if different from the participant's data):





          * Required field

          English