Predictive Analytics and AI

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  • 6500 GBP$ 4 weeks
  • Instructor

City
Duration
Year
Venue Start Date End Date Net Fees Details & Registration
Rome June 16, 2025 June 20, 2025 6500 GBP PDF Register

About course

In the era of data-driven decision-making, organizations are increasingly turning to predictive analytics and artificial intelligence to enhance their strategic capabilities. This professional training program aims to equip participants with the essential skills and knowledge needed to effectively leverage these technologies. By understanding the fundamental principles of data analysis and machine learning, attendees will be able to transform raw data into actionable insights that drive improved business outcomes. The course covers predictive modeling techniques, algorithm selection, and the integration of AI tools within organizational frameworks, with a strong focus on real-world applications. It also addresses ethical considerations related to data and AI usage, ensuring responsible practices. The curriculum provides a comprehensive understanding of both theoretical concepts and practical implementations, enabling participants to develop and deploy predictive models that anticipate trends and support informed decision-making. Ultimately, this program empowers professionals to navigate the complexities of data analytics and artificial intelligence, fostering a culture of innovation and analytical excellence within their teams.  

The Objectives

  • Understand the fundamentals of predictive analytics and AI.
  • Learn to develop predictive models using various techniques.
  • Gain insights into the integration of AI in business processes.
  • Explore ethical considerations in AI and data analytics.
  • Enhance decision-making capabilities through data-driven insights.
  • Foster collaboration and communication skills in analytics teams.

Training Methodology

The training will employ a blend of instructional methods, including interactive lectures, hands-on workshops, case studies, and group discussions. Participants will engage in practical exercises that reinforce learning and provide opportunities for applying concepts in real-world scenarios. Collaborative projects will encourage teamwork and knowledge sharing, ensuring a comprehensive learning experience.

Who Should Attend?

This course is ideal for professionals involved in data analysis, business intelligence, strategic planning, and decision-making processes. It is particularly beneficial for data analysts, business analysts, IT professionals, and managers seeking to enhance their understanding of predictive analytics and AI. Additionally, those interested in driving innovation within their organizations will find this training invaluable.

Detailed Outline

Day 1 Introduction to Predictive Analytics and AI
  • Overview of predictive analytics concepts
  • Understanding the role of AI in data analysis
  • Key terminologies and definitions
  • Types of predictive models
  • Data types and sources for analytics
  • Introduction to data exploration techniques
    Day 2 Data Preparation and Cleaning
  • Importance of data quality in analytics
  • Techniques for data cleaning and preprocessing
  • Data transformation methods
  • Handling missing values and outliers
  • Feature selection and engineering
  • Tools and software for data preparation
Day 3 Statistical Foundations for Predictive Modeling
  • Overview of statistical concepts relevant to analytics
  • Probability distributions and their applications
  • Hypothesis testing and confidence intervals
  • Correlation and regression analysis
  • Introduction to time series analysis
  • Evaluating model performance metrics
Day 4 Machine Learning Algorithms
  • Overview of machine learning concepts
  • Supervised vs. unsupervised learning
  • Introduction to classification algorithms
  • Regression techniques and their applications
  • Clustering methods and use cases
  • Model selection and validation techniques
Day 5 Implementing AI Solutions
  • Overview of AI technologies and frameworks
  • Integrating AI into business processes
  • Developing AI-driven predictive models
  • Ethical considerations in AI deployment
  • Case studies of successful AI implementations

Training Method?

  • Pre-assessment
  • Live group instruction
  • Use of real-world examples, case studies and exercises
  • Interactive participation and discussion
  • Power point presentation, LCD and flip chart
  • Group activities and tests
  • Each participant receives a copy of the presentation
  • Slides and handouts

Training Method?

The course agenda will be as follows:
  • Technical Session 30-10.00 am
  • Coffee Break 00-10.15 am
  • Technical Session 15-12.15 noon
  • Coffee Break 15-12.45 pm
  • Technical Session 45-02.30 pm
  • Course Ends 30 pm
       
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