Data Science for Business

  • About the course

    Any company collects data: data analytics is already helping businesses reduce costs, speed up delivery, and generate forecasts to make better decisions. And companies are increasingly looking to take advantage of Data Science to be competitive.

    In addition to professional Data Scientists, businesses also need Big Data-oriented employees who can identify opportunities to solve business problems using advanced analytics.

  • Upcoming events

    • The group is being formed

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  • Who might be interested

  • The course is prepared for a wide audience:

    • Owners and managers of companies,
    • Development Directors and Business Development Managers,
    • Employees of functional departments (HR, marketing, sales, service),
    • Business analysts,
    • Project managers and project office specialists.
  • Course program

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    1. Introduction to Data Science and Machine Learning:

    • Exponential thinking and technology.
    • Differences between concepts and projects of Business Intelligence, Data Science, Machine Learning, Artificial Intelligence. Structure of Data Science.
    • Scenarios of using and applying ML in the modern world.
    • Overview of successful Machine Learning projects.
    • Overview of popular frameworks and tools for Data Science solutions.
    • Introduction to Big Data.
    • Workshop 1: Innovative thinking.

    2. Data Science Processes and Frameworks:

    • Introduction to cognitive services.
    • Blockchain technology.
    • Historical review of data science decision making methodologies.
    • A detailed overview of the modern Data Science process and its stages.
    • Team and roles of specialists in Data Science projects.
    • Workshop 2: Business Understanding data science stage of the project.

    3. Data preprocessing and visualization:

    • Loading initial data for analysis into the system (ETL).
    • Data cleansing and transformation.
    • Data Sampling and Quantization.
    • Workshop 2: Preparing data for the project.
    • Approaches and techniques for data visualization.
    • Practice: Data vizualization with Power BI.

    4. Prediction and classification:

    • Theoretical overview of the problem and basic methods.
    • Introduction to artificial neural networks for solving various problems.
    • The process of creating real software models for prediction and classification.
    • Evaluation of the accuracy of trained models, selection of the best one.
    • Workshop 3: Building prediction and classification models.

    5. Clustering and recommendation algorithms:

    • Introduction to analysis and forecasting of time series.
    • Theoretical overview of the problem and basic methods.
    • The process of creating real software models for clustering, recommendation algorithms.
    • Evaluation of the accuracy of trained models, selection of the best one.
    • Workshop 4: Creation of clustering and recommendation models.

    6. Implementation of machine learning models:

    • Introduction to computer vision and pattern recognition.
    • Implementation of machine learning models for further use.
    • Examples of architectures of a full-fledged project.
    • Workshop 5: Implementation of machine learning models.
    • Introduction to natural language processing.
    • Recommended materials and steps for further studying.
  • Format

  • The course combines lecture blocks and practice: working with real data in the Azure environment.

    Requirements:

    • Basic knowledge of algebra and mathematical statistics,
    • Knowledge of English at the Intermediate level.
  • Trainer

  • Andrii Belas is an expert in the field of machine learning, a public speaker. Leading Data Scientist at SMART business, has a number of successful projects in the areas of predictive analytics and computer vision. Creator and mentor of SMART Data Science Academy, responsible for the technical development of the data science team and the architecture of all data science projects of SMART business.
    Microsoft Certified Professional in Big Data and Advanced Analytics, Cloud Data Science with Azure Machine Learning, Developing SQL Data Models.

  • Cost

  • The cost of participation in the course is UAH 12 000, without VAT.

  • Save together!

  • 2 people registered – a 10% discount is provided.
    When registering 3 or more people, an individual decision is made on the payment amount.