Free Download Terraform Fundamentals Infrastructure as Code, Providers, and State for Terraform Associate (004)
Released 3/2026
By Ned Bellavance
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 56m 53s | Size: 166 MB
Managing infrastructure manually is error-prone and time-consuming, making it difficult to scale and maintain consistency across environments.
What you’ll learn
Managing infrastructure manually is error-prone and time-consuming, making it difficult to scale and maintain consistency across environments. In this course, Terraform Fundamentals: Infrastructure as Code, Providers, and State for Terraform Associate (004), you’ll gain the ability to deploy and manage infrastructure using Terraform. First, you’ll explore infrastructure as code concepts and Terraform’s role in the IaC landscape. Next, you’ll discover how to work with Terraform providers to interact with different platforms. Finally, you’ll learn how to manage Terraform state to track your infrastructure. When you’re finished with this course, you’ll have the skills and knowledge of Terraform fundamentals needed to deploy and manage infrastructure using Terraform.
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reprocess natural language text to be used with a neural networkCreate word embeddings (numerical representations of text) with TensorFlowBuild neural networks capable of binary and multi-class classification using:RNNs (recurrent neural networks)LSTMs (long short-term memory cells)GRUs (gated recurrent units)CNNsLearn how to evaluate your NLP models9 – Milestone Project 2: SkimLit Replicate a the model which powers the PubMed 200k paper to classify different sequences in PubMed medical abstracts (which can help researchers read through medical abstracts faster)10 – Time Series fundamentals in TensorFlowLearn how to diagnose a time series problem (building a model to make predictions based on data across time, e.g. predicting the stock price of AAPL tomorrow)Prepare data for time series neural networks (features and labels)Understanding and using different time series evaluation methodsMAE – mean absolute errorBuild time series forecasting models with TensorFlowRNNs (recurrent neural networks)CNNs (convolutional neural networks)11 – Milestone Project 3: (Surprise)If you’ve read this far, you are probably interested in the course. This last project will be good. we promise you, so see you inside the course 
TensorFlow is growing in popularity and more and more job openings are appearing for this specialized knowledge. As a matter of fact, TensorFlow is outgrowing other popular ML tools like PyTorch in job market. Google, Airbnb, Uber, DeepMind, Intel, IBM, Twitter, and many others are currently powered by TensorFlow. There is a reason these big tech companies are using this technology and you will find out all about the power that TensorFlow gives developers. We guarantee you this is the most comprehensive online course on TensorFlow. So why wait? Make yourself stand out by becoming a TensorFlow Expert and advance your career.See you inside the course!
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