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Sequences, Time Series and Prediction

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new DeepLearning.AI TensorFlow Developer Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.
Duration 7 Months
Institution DeepLearning.AI
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into DeepLearning.AI.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $327
Total Est. Investment $327

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Sequences, Time Series and Prediction program at DeepLearning.AI are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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