TensorFlow Developer Certificate - Time Series, Sequences, and Predictions from Pluralsight

TensorFlow is a powerful open-source library for machine learning and numerical computation to develop and train deep learning models. This course will teach you how to analyze time series data and accurately forecast future events.

Forecasting key business metrics accurately is crucial for making smart decisions and planning for the future. In this course, TensorFlow Developer Certificate - Time Series, Sequences, and Predictions, you’ll gain the ability to build predictive models for time series data using deep learning.

First, you’ll explore how to structure time series problems and preprocess data for modeling.

Next, you’ll discover how to choose and configure deep learning models like RNNs and CNNs for sequence forecasting tasks.

Finally, you’ll learn best practices for training, evaluating, and improving your forecasts over time.

When you’re finished with this course, you’ll have the skills and knowledge of TensorFlow and deep learning for time series needed to accurately forecast metrics like future sales, demand, stock prices, and more.

What's inside

Syllabus

Course Overview

Understanding and Preparing Time Series Data

Training and Evaluating Time Series Models

Implementing Advanced Techniques for Time Series Analysis

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a strong foundation for beginners in time series prediction

Teaches industry-standard tools for time series analysis: TensorFlow, RNNs, and CNNs

Covers advanced techniques for time series analysis, such as forecasting with uncertainty

Taught by Pinal Dave, a recognized expert in TensorFlow and deep learning

Requires learners to come in with some background knowledge in machine learning

Focuses on practical skills and provides hands-on labs for learners to apply their knowledge

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 TensorFlow Developer Certificate - Time Series, Sequences, and Predictions with these activities:

Review course syllabus and assignments

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Gather and review all course materials to establish a foundational understanding of the expectations and requirements.

Browse courses on Course Syllabus

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Download the course syllabus and review
Gather and organize any additional assignments

Review basic machine learning concepts

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Strengthen the foundation for time series analysis by reviewing fundamental machine learning concepts.

Browse courses on Machine Learning

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Review supervised and unsupervised learning methods
Brush up on performance evaluation metrics

Read deeper into time series analysis

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Enhance theoretical knowledge and gain a comprehensive understanding of time series analysis principles and applications by reading a recommended book.

View Forecasting: Principles and Practice on Amazon

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Obtain the book and dedicate time for reading
Actively engage with the material by taking notes and reflecting on key concepts

Four other activities

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Solve time series analysis practice problems

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Enhance understanding and refine problem-solving skills by working through practice problems related to time series analysis.

Browse courses on Time Series Analysis

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Find practice problems in textbooks, online resources, or course materials
Attempt to solve the problems independently
Review solutions and identify areas for improvement

Participate in online time series analysis discussions

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Engage with peers to exchange ideas, ask questions, and enhance understanding of time series analysis concepts.

Browse courses on Time Series Analysis

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Join online forums or discussion boards related to time series analysis
Actively participate by sharing insights and asking for feedback

Develop a personal time series analysis project

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Apply the concepts learned in the course to a practical project, reinforcing understanding and fostering hands-on experience.

Browse courses on Time Series Analysis

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Identify a suitable time series dataset
Choose a machine learning model and configure it for time series analysis
Train and evaluate the model using real-world data

Follow tutorials on advanced techniques for time series analysis

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Expand knowledge and skills by exploring tutorials on advanced time series analysis methods.

Browse courses on Advanced Techniques

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Identify tutorials covering advanced techniques like ARIMA, SARIMAX, and LSTM
Follow the tutorials and work through the examples

Career center

Learners who complete TensorFlow Developer Certificate - Time Series, Sequences, and Predictions will develop knowledge and skills that may be useful to these careers:

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course will help you develop the skills needed to apply deep learning techniques to time series analysis in order to make better decisions. By learning how to choose and configure deep learning models, you'll be able to develop optimization and forecasting models that can improve operational efficiency.

See salaries and explore the career path for Operations Research Analyst

Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course will help you build a foundation in time series analysis, which is essential for understanding and predicting risk over time. By learning how to structure time series problems and evaluate forecasts, you'll be able to more accurately assess risk and develop more effective risk management strategies.

See salaries and explore the career path for Actuary

Financial Risk Manager

Financial Risk Managers identify, assess, and manage financial risks within an organization. This course will help you develop the skills needed to apply deep learning techniques to time series analysis in order to identify and manage risk. By learning how to choose and configure deep learning models, you'll be able to develop risk management models that can help organizations make better decisions.

See salaries and explore the career path for Financial Risk Manager

Data Engineer

Data Engineers design, build, and maintain data pipelines to collect, clean, and process data. This course will help you develop the skills needed to apply deep learning techniques to time series analysis in order to design and build more effective data pipelines. By learning how to choose and configure deep learning models, you'll be able to develop data pipelines that can accurately forecast future events and provide valuable insights.

See salaries and explore the career path for Data Engineer

Data Architect

Data Architects design and build data systems to meet the needs of an organization. This course will help you develop the skills needed to apply deep learning techniques to time series analysis in order to design and build more effective data systems. By learning how to choose and configure deep learning models, you'll be able to develop data systems that can accurately forecast future events and provide valuable insights.

See salaries and explore the career path for Data Architect

Quantitative Analyst

Quantitative Analysts seek profitable investment strategies by modeling financial and economic data. This course can be a part of a larger approach to gain the computational knowledge needed to succeed in this role. By learning how to select deep learning models and apply techniques for time series modeling, you'll build a solid foundation for developing financial models that make accurate predictions.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts perform detailed research and write reports on business trends, investment strategies, and potential opportunities. This course's emphasis on applying deep learning models to forecast future events will give you a significant advantage in creating data-driven insights and recommendations.

See salaries and explore the career path for Financial Analyst

Machine Learning Engineer

Machine Learning Engineers build, deploy, and maintain machine learning models. This course will help you build the skills to develop and implement sequence forecasting models. By gaining proficiency in these models, you'll be well-equipped to create solutions that capture temporal dependencies and predict future events.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use scientific methods and programming to extract knowledge and insights from data. This course can help you develop the technical skills needed to specialize in time series analysis. By learning how to structure time series problems and evaluate forecasts, you'll be able to effectively analyze and interpret time-dependent data.

See salaries and explore the career path for Data Scientist

Research Analyst

Research Analysts conduct research and analysis to provide insights and recommendations on a variety of topics. This course will help you build a strong foundation in using deep learning for time series modeling. By gaining proficiency in these techniques, you'll be able to extract valuable insights from historical data and make informed predictions about future trends.

See salaries and explore the career path for Research Analyst

Data Analyst

Data Analysts collect, clean, analyze, and interpret data to provide insights and make recommendations. This course may be useful in helping you build the skills needed to specialize in time series analysis. By learning how to structure time series problems and preprocess data, you'll be able to effectively analyze and interpret time-dependent data.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts identify and solve business problems by analyzing data and developing solutions. This course will help you gain the skills needed to analyze time series data and make accurate forecasts. By learning how to preprocess data and evaluate models, you'll be able to provide valuable insights and recommendations to businesses.

See salaries and explore the career path for Business Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course may be useful in helping you build the technical skills needed to specialize in time series analysis software development. By learning how to implement advanced techniques for time series analysis, you'll be able to develop software solutions that can accurately forecast future events.

See salaries and explore the career path for Software Engineer

Consultant

Consultants provide expert advice and guidance to organizations on a variety of topics. This course may be useful in helping you build the skills needed to specialize in time series analysis consulting. By learning how to structure time series problems and evaluate forecasts, you'll be able to effectively analyze and interpret time-dependent data, providing valuable insights and recommendations to organizations.

See salaries and explore the career path for Consultant

Statistician

Statisticians collect, analyze, interpret, and present data to help organizations make informed decisions. This course may be useful in helping you build the skills needed to specialize in time series analysis. By learning how to structure time series problems and evaluate forecasts, you'll be able to effectively analyze and interpret time-dependent data.

See salaries and explore the career path for Statistician

TensorFlow Developer Certificate - Time Series, Sequences, and Predictions

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