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Victoria Clark

Learn one of the key concepts of Financial Management: financial forecasting, and how to automate key steps in your forecasting process with Python.

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Learn one of the key concepts of Financial Management: financial forecasting, and how to automate key steps in your forecasting process with Python.

Automate Financial Forecasting tasks with Python. In this course, Automate Forecasting in Python 3, you will learn how to automate key steps of the Financial Forecasting process. First, you will learn core Financial Management concepts, including the importance of big data in building a forecast. Next, you will discover how to use Python to collect data from different sources, including external APIs and how to use Python to clean data for use. Finally, you will explore how to ensure your data is up to date using SQLite and Python, and how to visually express your forecast in Python. When you’re finished with this course, you will have the skills and knowledge of building a relevant forecast that is automated by Python. Software required: Juypiter Notebook, SQLite, Python 3.6 or later

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What's inside

Syllabus

Course Overview
Understanding What Makes a Good Forecast
Building a Forecast: Collecting and Converting Data
Building a Forecast: Ensuring Data Is Up-to-date
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Building a Forecast: Visual Expression

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Victoria Clark, who is an experienced instructor in Financial Management and Forecasting
Builds a strong foundation in core Financial Management concepts, including the importance of big data in forecasting
Explores up-to-date methods for automating key steps in the forecasting process with Python
Develops skills in data collection, cleaning, and visualization, which are essential for effective forecasting
Suitable for learners with a background in finance or business who want to enhance their forecasting capabilities with Python

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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 Financial Management: Automate Forecasting in Python 3 with these activities:
Review Financial Management Concepts
Refine your knowledge of financial management concepts to ensure a strong foundation for the course.
Browse courses on Financial Management
Show steps
  • Review course syllabus and identify key concepts
  • Read textbooks and articles on financial management
  • Take online quizzes or practice problems
Read 'Introduction to Financial Management' by Eugene Brigham and Joel Houston
Gain a comprehensive understanding of financial management principles from a highly-regarded textbook.
Show steps
  • Read each chapter thoroughly
  • Take notes and highlight key concepts
  • Complete end-of-chapter exercises
Solve Financial Forecasting Practice Problems
Enhance your ability to apply financial forecasting techniques through repetitive practice.
Browse courses on Financial Forecasting
Show steps
  • Find practice problems or online resources
  • Solve problems using Python
  • Check your solutions and analyze your mistakes
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow Tutorials on Python for Financial Forecasting
Expand your knowledge of Python and its applications in financial forecasting.
Show steps
  • Identify tutorials on reputable platforms
  • Follow tutorials step-by-step
  • Build small projects to apply your learning
Develop a Financial Forecasting Model
Apply your skills to build a practical financial forecasting model that solves a real-world problem.
Show steps
  • Define the problem and gather data
  • Choose appropriate Python libraries
  • Create and implement the model
  • Evaluate and refine the model
Participate in Financial Forecasting Competitions
Challenge yourself and test your forecasting skills against others in a competitive environment.
Show steps
  • Find and register for relevant competitions
  • Form a team or work individually
  • Develop and refine your forecasting model
Mentor Junior Students in Financial Forecasting
Reinforce your understanding of financial forecasting concepts while helping others learn.
Browse courses on Mentoring
Show steps
  • Volunteer as a mentor
  • Meet with mentees regularly
  • Provide guidance and support

Career center

Learners who complete Financial Management: Automate Forecasting in Python 3 will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use data to build models that can solve business problems. This course teaches how to use Python to automate the collection, cleaning, and analysis of data, which are essential skills for Data Scientists. The course also covers data visualization, which is essential for communicating findings to stakeholders.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to solve complex business problems. This course teaches how to automate the development and analysis of financial models, which are key skills for Quantitative Analysts. The course also covers data collection and visualization, which are essential for building and interpreting models.
Statistician
Statisticians use data to solve problems and make predictions. This course teaches how to use Python to automate the collection and analysis of data, which can save Statisticians time and help them make more accurate predictions.
Investment Analyst
Investment Analysts evaluate investment opportunities and make recommendations to clients. This course teaches how to use Python to automate the collection and analysis of financial data, which is essential for making investment decisions. The course also covers data visualization, which is helpful for communicating findings to clients.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. This course teaches how to use Python to automate the development and analysis of financial models, which are key skills for Operations Research Analysts. The course also covers data collection and visualization, which are essential for building and interpreting models.
Financial Analyst
Financial Analysts develop financial models and forecasts to help businesses make investment decisions. This course teaches how to automate the development of financial forecasts, which can save Financial Analysts time and help them make more accurate predictions.
Risk Analyst
Risk Analysts identify and assess risks to businesses. This course teaches how to use Python to automate the collection and analysis of data to create risk models. The course also covers data visualization, which is helpful for communicating findings to stakeholders.
Data Engineer
Data Engineers build and maintain data infrastructure for businesses. This course teaches how to use Python to automate the collection, cleaning, and analysis of data, which are essential skills for Data Engineers. The course also covers data visualization, which is helpful for communicating findings to stakeholders.
Actuary
Actuaries use mathematical and statistical models to assess and manage risk in the insurance industry. This course teaches how to use Python to automate the development and analysis of financial models, which are key skills for Actuaries. The course also covers data collection and visualization, which are essential for building and interpreting models.
Economist
Economists use data to study the economy and make recommendations to policymakers. This course teaches how to use Python to automate the collection and analysis of economic data, which can save Economists time and help them make more accurate predictions.
Business Analyst
Business Analysts gather and analyze data to help businesses understand their operations and make better decisions. This course teaches how to use Python to automate the collection and analysis of data, which can save Business Analysts time and help them make more accurate recommendations.
Data Analyst
Data Analysts gather, clean, and analyze data to help businesses understand market trends and make better decisions. This course teaches how to automate the collection, cleaning, and analysis of data, which are necessary skills for Data Analysts. The course also covers how to visualize data, which is essential for communicating findings to stakeholders.
Management Consultant
Management Consultants help businesses solve problems and improve their operations. This course teaches how to use Python to automate the collection and analysis of data, which can save Management Consultants time and help them make more accurate recommendations.
Financial Planner
Financial Planners help individuals and families plan for their financial future. This course teaches how to use Python to automate the collection and analysis of financial data, which can save Financial Planners time and help them make more accurate recommendations.
Software Engineer
Software Engineers develop and maintain software applications. This course teaches how to use Python to automate the collection, cleaning, and analysis of data, which can be helpful for Software Engineers who want to develop data-driven applications.

Reading list

We've selected 12 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 Financial Management: Automate Forecasting in Python 3.
Provides a comprehensive overview of forecasting methods, serving as a valuable reference for understanding the theoretical underpinnings of the techniques used in the course.
Serves as a comprehensive guide to using Python for data analysis, providing a solid foundation for the Python skills used in the course.
Provides a specialized guide to financial time series forecasting using Python, complementing the course's focus on automation with specific financial applications.
Offers a comprehensive reference for Python data science tools and libraries, providing a valuable resource for implementing the techniques covered in the course.
Provides a comprehensive guide to using the SQLAlchemy library for database interaction in Python, offering a valuable resource for working with data in the course.
Provides an accessible introduction to machine learning using Python, offering a foundation for those who may be new to the field.
Explores the application of machine learning techniques in asset management, providing a broader perspective on the use of data-driven approaches in financial forecasting.
Focuses on time series analysis and forecasting techniques, offering practical examples and case studies that reinforce the concepts covered in the course.
Provides a practical introduction to deep learning using the Fastai and PyTorch libraries in Python, offering insights into advanced data analysis techniques that complement the course's focus on automation.
Offers a broader perspective on data science in a business context, providing insights into the role of forecasting within the larger field.

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