In the modern business world, companies are witnessing a major transformation in the way they formulate their strategies and make decisions thanks to the rapid advancement of machine learning technologies. Machine learning, as a branch of artificial intelligence, represents a revolution in how data is analyzed, future trends are predicted, and the ability to make strategic decisions based on accurate and scientific insights.
Strategic management is one of the fundamental aspects that determine the success of organizations in a rapidly changing market. It involves setting long-term goals, planning how to achieve these goals, and assessing the competitive environment. In this context, machine learning provides powerful tools to significantly improve these processes. By leveraging technologies such as big data analytics, predictive modeling, and machine learning, companies can gain more accurate strategic insights and make informed decisions based on reliable data.
Machine learning enables strategic management to deal with the complexities of data more effectively, and provide predictive models that can forecast economic and market trends before they happen. It also enhances the ability to analyze customer behavior, understand market needs, and identify opportunities and threats more accurately. Instead of relying solely on trial and error, these technologies provide advanced analysis tools that make it possible to design strategies based on concrete data facts.

Who Should Attend?

• Executives and senior managers.
• Strategy and planning managers.
• Strategic analysts.
• Business consultants and strategic advisors.
• Project managers and supervisors.
• Marketing and data analytics managers.
• Entrepreneurs and startup owners.
• Academicians and researchers in management and technology.

Knowledge and Benefits:

After completing the program, participants will be able to master the following:

• Concepts of machine learning, deep learning, and types of algorithms used.
• Collecting and analyzing relevant data using machine learning techniques.
• Using machine learning-based analytics to develop and improve business strategies.
• Using the results derived from the analysis to make more accurate and effective strategic decisions.
• Using machine learning techniques to monitor and analyze business performance and key indicators.
• Analyzing performance gaps and developing strategies to improve efficiency and effectiveness.

• Introduction to Machine Learning and Strategic Management
  • Definition of machine learning, deep learning, and types of algorithms.
  • Comparison between supervised and unsupervised learning.
  • Principles of strategic management and the importance of data analysis in developing business strategies.
  • How to integrate machine learning into the strategic planning process.
• Collect and analyze strategic data using machine learning
  • Data sources in business (customer data, market data, performance data).
  • Tools and techniques for collecting big data.
  • Data cleaning and analysis techniques.
  • Applying machine learning techniques to analyze data and extract strategic insights.
• Building predictive models to develop strategies
  • How to build predictive models using machine learning algorithms.
  • Techniques for improving model performance.
• Improving business strategies through data analytics
  • Using predictive analytics to develop effective business strategies.
  • Examples of improving marketing, sales, and operations management strategies.
  • Applying analysis results to improve business strategies.
• Enhancing strategic decision-making ability using machine learning
  • Using insights derived from machine learning in the strategic decision-making process.
  • Using machine learning to analyze risks and opportunities and making strategic decisions based on comprehensive analysis.
• Performance Management and Analytics with Machine Learning
  • Using machine learning to monitor and analyze business performance and key indicators.
  • Using machine learning tools to identify performance gaps and develop improvement strategies.
• Ethical and regulatory issues in the use of machine learning
  • Ethical issues associated with the use of machine learning in data analysis and decision making.
  • Laws and regulations governing the use of machine learning in business.