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Dr. Rafif Srour Daher

This course aims to provide you with a robust understanding of forecasting and predictive analytics. You will gain the knowledge and skills necessary to apply these techniques in real-world scenarios, while identifying the challenges of changing processes and supporting stakeholders during transitions. You’ll also be guided on the methods of estimating future business outputs based on historical data and unpack ways that businesses can use forecasting techniques to gain insight into future demand. You will discover how to use time-series forecasting to better anticipate future trends. You will develop a holistic approach to using predictive analytics in business, considering the different stages of a data analytics pipeline, and learn how to use predictive models to support strategic decision-making. The factors for successful deployment of a predictive model, data quality, governance, and stakeholder buy-in will also be analyzed.

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This course aims to provide you with a robust understanding of forecasting and predictive analytics. You will gain the knowledge and skills necessary to apply these techniques in real-world scenarios, while identifying the challenges of changing processes and supporting stakeholders during transitions. You’ll also be guided on the methods of estimating future business outputs based on historical data and unpack ways that businesses can use forecasting techniques to gain insight into future demand. You will discover how to use time-series forecasting to better anticipate future trends. You will develop a holistic approach to using predictive analytics in business, considering the different stages of a data analytics pipeline, and learn how to use predictive models to support strategic decision-making. The factors for successful deployment of a predictive model, data quality, governance, and stakeholder buy-in will also be analyzed.

What you'll learn

  • Evaluate projected demands to optimize supply chain operations.

  • Choose appropriate forecasting techniques based on business objectives.

  • Identify key considerations when adding new predictive elements to a workflow, such as data quality, data integration, and data governance.

  • Apply change management strategies to effectively deploy data-driven processes in organizations.

  • Evaluate the practical applications, strengths, and limitations of predictive analytics.

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Designed for learners who need to develop skills in forecasting and predictive analytics to use in business and other fields
Teaches foundational concepts in forecasting and predictive analytics, including definitions, techniques, and applications
Help learners gain practical experience with real-world scenarios and case studies
Provides guidance on the methods of estimating future business outputs based on historical data and unpacks ways that businesses can use forecasting techniques to gain insight into future demand
Covers how to use time-series forecasting to better anticipate future trends

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Predictive Analytics for Business Planning: Time-Series Forecasting with these activities:
Review basics of statistics
Ensure you have a strong foundation in basic statistical principles before the course starts to help you better understand the principles of forecasting.
Browse courses on Statistics
Show steps
  • Review the topics of mean, median, mode, and standard deviation
  • Take a practice test on basic probability
  • Go over the basics of creating and interpreting graphs
Join a study group with classmates
Collaborating with peers in a study group can enhance your understanding of course material through discussions, shared resources, and feedback.
Show steps
  • Reach out to classmates to form a study group
  • Establish a regular meeting schedule
  • Work together to review course material, solve problems, and prepare for assessments
Read Predictive Analytics for Dummies
Strengthen foundational understanding of predictive analytics concepts.
Show steps
  • Review key concepts and techniques in predictive analytics.
  • Gain insights into practical applications of predictive analytics.
Ten other activities
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Follow Tutorials on Data Analysis with Python
Enhance data analysis skills with Python, complementing the course's focus on forecasting.
Browse courses on Data Analysis
Show steps
  • Identify online tutorials on data analysis with Python.
  • Complete the tutorials, practicing data manipulation and analysis techniques.
Practice time-series forecasting
Performing repetitive exercises will help you internalize the principles of time-series forecasting and strengthen your grasp of the material covered in the course.
Browse courses on Time-Series Forecasting
Show steps
  • Use statistical software such as R or Python to practice creating time-series models
  • Find real-world datasets to practice time-series forecasting
  • Evaluate the accuracy of your models using various metrics
Practice Forecasting Techniques
Gain practical experience applying forecasting techniques to real-world scenarios.
Show steps
  • Select a forecasting technique based on business objectives.
  • Gather historical data relevant to the forecast.
  • Apply the selected technique to the historical data.
  • Evaluate the accuracy of the forecast.
Join Study Group for Course Concepts
Enhance understanding through collaboration and discussion with peers.
Show steps
  • Form or join a study group with other course participants.
  • Discuss course concepts, share insights, and clarify doubts.
Attend Workshop on Predictive Analytics in Business
Gain exposure to industry-specific applications and best practices in predictive analytics.
Show steps
  • Identify relevant workshops on predictive analytics applications in business.
  • Attend the workshop, take notes, and engage in discussions.
Attend a workshop on data-driven decision-making
Attending an industry workshop can broaden your understanding of how forecasting and predictive analytics are applied to solve real-world business problems.
Show steps
  • Identify and register for a workshop relevant to data-driven decision-making
  • Attend the workshop and actively participate in discussions
Develop Predictive Analytics Case Study
Reinforce understanding of predictive analytics by applying it to a specific business problem.
Browse courses on Case Study Analysis
Show steps
  • Identify a business problem that can be addressed with predictive analytics.
  • Gather and analyze data relevant to the problem.
  • Develop and apply predictive models to the data.
  • Evaluate the performance of the models.
  • Present the case study, including insights and recommendations.
Participate in Kaggle Competition on Forecasting
Apply forecasting skills in a competitive environment, enhancing problem-solving abilities.
Browse courses on Kaggle Competitions
Show steps
  • Identify relevant Kaggle competitions focused on forecasting.
  • Develop and submit forecasting models to the competition.
Develop a predictive model for a real-world business problem
Applying the concepts covered in the course to a real-world problem will provide hands-on experience and deepen your understanding of the practical applications of forecasting and predictive analytics.
Show steps
  • Identify a business problem suitable for predictive modeling
  • Gather and clean the necessary data
  • Develop a predictive model using appropriate techniques
  • Evaluate the model's performance and make necessary adjustments
  • Present the model and findings to stakeholders
Contribute to Open-Source Predictive Analytics Project
Gain hands-on experience with practical implementation of predictive analytics.
Show steps
  • Identify open-source projects related to predictive analytics.
  • Contribute to the project by reporting bugs, fixing issues, or enhancing features.

Career center

Learners who complete Predictive Analytics for Business Planning: Time-Series Forecasting will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst provides actionable information for decision-making across the company. They are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Data Analyst. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Business Analyst
A Business Analyst is responsible for understanding the needs of a business and translating those needs into technical requirements. They work with stakeholders to gather requirements, analyze data, and develop solutions. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Business Analyst. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.
Market Research Analyst
A Market Research Analyst is responsible for gathering and interpreting data about markets, customers, and competitors. They use this information to help businesses make informed decisions about product development, marketing campaigns, and pricing. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Market Research Analyst. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Financial Analyst
A Financial Analyst is responsible for analyzing financial data to make recommendations about investments and financial decisions. They use their knowledge of financial markets and economic trends to help businesses make informed decisions about capital allocation, risk management, and mergers and acquisitions. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Financial Analyst. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Operations Research Analyst
An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve business problems. They work with businesses to improve efficiency, reduce costs, and increase profits. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as an Operations Research Analyst. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Data Scientist
A Data Scientist is responsible for developing and implementing predictive models to solve business problems. They work with businesses to collect, clean, and analyze data to identify trends and patterns. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Data Scientist. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. They work with businesses to identify trends, patterns, and opportunities. The Predictive Analytics for Business Planning: Time-Series Forecasting course will help you develop the skills needed to succeed as a Business Intelligence Analyst. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Management Consultant
A Management Consultant is responsible for providing advice to businesses on a variety of topics, including strategy, operations, and finance. They work with businesses to identify problems, develop solutions, and implement change. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Management Consultant. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.
Product Manager
A Product Manager is responsible for developing and launching new products. They work with engineers, designers, and marketers to bring products to market. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Product Manager. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns. They work with a variety of stakeholders to create and implement marketing strategies. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Marketing Manager. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Sales Manager
A Sales Manager is responsible for leading and motivating a sales team. They work with sales representatives to develop and execute sales strategies. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Sales Manager. You will learn how to use time-series forecasting to better anticipate future trends and develop a holistic approach to using predictive analytics in business.
Account Manager
An Account Manager is responsible for managing relationships with key customers. They work with customers to identify their needs and develop solutions. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as an Account Manager. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.
Customer Success Manager
A Customer Success Manager is responsible for ensuring that customers are satisfied with their products or services. They work with customers to resolve problems, provide support, and identify opportunities for growth. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Customer Success Manager. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.
Project Manager
A Project Manager is responsible for planning, executing, and closing projects. They work with a variety of stakeholders to ensure that projects are completed on time, within budget, and to the required quality. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Project Manager. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.
Consultant
A Consultant is responsible for providing advice and support to businesses on a variety of topics. They work with businesses to identify problems, develop solutions, and implement change. The Predictive Analytics for Business Planning: Time-Series Forecasting course may help you develop some of the skills needed to succeed as a Consultant. You will learn how to identify the challenges of changing processes and supporting stakeholders during transitions.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Predictive Analytics for Business Planning: Time-Series Forecasting.
Provides a comprehensive overview of predictive analytics, with a focus on the business applications of these techniques. It covers a wide range of topics, including data mining, machine learning, and statistical modeling.
Provides a practical guide to time series forecasting using Python. It covers a wide range of topics, including data preparation, model selection, and evaluation.
Provides a comprehensive overview of exponential smoothing methods for time series forecasting. It covers a wide range of topics, including the underlying statistical models, forecasting techniques, and applications.
Provides a comprehensive overview of time series analysis. It covers a wide range of topics, including stationary processes, non-stationary processes, and forecasting.
Provides a comprehensive overview of time series analysis and forecasting. It covers a wide range of topics, including stationary processes, non-stationary processes, and forecasting.
Provides a comprehensive overview of time series analysis and forecasting. It covers a wide range of topics, including stationary processes, non-stationary processes, and forecasting.
Provides a comprehensive overview of time series analysis and forecasting. It covers a wide range of topics, including stationary processes, non-stationary processes, and forecasting.

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