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Data Science and Predictive Analytics

Duration: 16 hours / 2 days

Knowledge: Intermediate

Potential trainer(s): Mateja Novaković, Goran Gvozden, Ivan Kesedžić, Kristijan Pavlović

Language: Croatian, English

Possible locations: PI EDU center, At client premises, Virtual education

Data Science is the most significant trend in the field of analytical data, which requires a wider picture of data related to data, analysis and presentation of data. Predictive analytics as a part of the field of data science gets more importance because traditional reports can answer the past and the present, but not the future.

Syllabus
Date 1
Soon
Price
*
390.00 EUR
2938.45 HRK
* Price per attendee, price without VAT 25%, conversion rate HRK > EUR 7,53450
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Overview

Predictive analytics has been the most significant trend in the field of data analytics in the last decade, where the focus is on predicting future outcomes based on patterns in past data. Using data science and predictive methodologies allows you to discover unknown business insights that you were not aware of in your data and to predict future events with a certain probability.

In this training, you will learn how to:
• Analyze and interpret the most important data elements using visualizations.
• Apply data science knowledge within your project.
• Ask analytical questions as a data analyst.
• Formulate and initiate data science projects using methodologies used by Poslovna Inteligencija consultants.
• Use predictive algorithms for predicting decision tree discounts and regression.
• Create neural networks using Keras and Tensorflow tools.
• Evaluate model performance and improve the model using various methods.
After actively participating in the Data Science and Predictive Analytics training, you will be ready to apply your data science experience to solving business challenges using your own data. This education is not only focused on applying algorithms for predictive analytics but on learning the entire data science process framework, which includes defining business problems and data sets, data processing, applying predictive models, and evaluating results.

Audience

The training is intended for participants with basic Python knowledge and conceptual understanding of programming.

  • Data analysts
  • Data scientists
  • IT development engineers
  • Project or product managers
  • Business users (controlling, finance, sales, marketing, human resources, etc.)
  • Statisticians
  • DWH/BI specialists.

What you will learn

  • I want to apply Data Science to innovate existing processes and products/services in my organization.
  • I want to learn a methodological framework for implementing Data Science projects according to industry practices.
  • I want to learn how to apply predictive algorithms to solve different analytical questions.
  • I want to improve my existing knowledge of predictive analytics.
  • I want to learn how to create my own algorithms and neural networks and how to validate and improve them.

Syllabus

  • 1. Introduction to data science

    In this module, you will learn what Data Science is, what it is used for, where it can be applied in business, and how to learn the skills required to work on Data Science projects.

    • Practical exercises include: advanced Python, NumPy, and Pandas

  • 2. Analysis, preparataion and processing of data for data science projects

    In this module, you will learn how to prepare and process data for Data Science projects so that predictive algorithms can provide meaningful and accurate results. During this module, you will learn how to merge data from multiple data sources, structure them, normalize, transform, and remove outliers.

    • Practical exercises include: Visualization (Matplotlib + Seaborn), Data preparation

  • 3. Predictive and descriptive analytics

    In this module, you will learn what descriptive and predictive analytics are and how to use them together to extract useful knowledge from data. You will also learn the most commonly used algorithms in predictive analytics such as regression, decision trees, logistic regression, clustering.

    • Practical exercises include: Linear regression, Decision tree (+Random Forest), Clustering

  • 4. Creation, evaluation and enhancement of predictive algorithms

    In this module, you will have the opportunity to learn how to create your own algorithms and neural networks and adapt them to the specific needs of your project. Instead of relying on plug-and-play solutions, which are often not sufficiently tailored to your needs, you will learn how to create your own models that will allow you to achieve more precise and high-quality results.

    • Practical exercises include: Neural network

  • 5. Project – applying predictive algorithms

    In this module, you will apply the theory and practice learned to a concrete example using all the tools covered in this education. In this module, you will predict whether a patient sent to ER will survive based on certain data.

    • Practical exercises include: Project description and data for the project
FAQ – frequently asked questions
How can I register for this training?

You can officially register for the training via the registration form at the top of this page. After successfully sending the application, we will get back to you within 24 hours of receiving the application.

I have not received any feedback from you. Who should I contact?

Mistakes in communication always happen, and if we don’t answer you, contact us directly at birdacademy@inteligencija.com

Can training be paid in several installments?

We currently do not support payment in multiple installments.

I don't live in Zagreb, but I would like to attend the training virtually. Is there such a possibility?

Of course, all our trainings can be followed virtually.

Is there a discount for students?

Students are entitled to a 10% discount on the price shown on this page.

I don't have my own laptop for this training. Do you provide me with a computer for training?

BIRD Academy provides a computer, lunch, coffee and water for each participant. We strive to be the best host possible in every segment!

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