Packt Publishing – Amazon Bedrock And Q Developer For Python 2026 BOOKWARE-LERNSTUF | Apps-Tutorials | MKV | 1.04 GiB
648 kb/s 1280×720 | AAC 128 kb/s 2 CH
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Packt Publishing
Amazon Bedrock And Q Developer For Python
2026
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.. - - - /- --- _- [ R E L E A S E D E T A i L S ]- . ./\ . - __./---'
Release Date : 2026-07-15
Publisher : Packt Publishing
Title : Amazon Bedrock And Q Developer For Python
Year : 2026
Month : 07
Category : Unknown
Language : English
Section : BOOKWARE
Files : 03 x 400 MB
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https://learning.oreilly.com/videos/-/9781808491832/
In this 4-hour course, you will learn how to build generative AI applications
using Amazon Bedrock, Amazon Q Developer, and Python on AWS. Explore
foundation models, prompt engineering, model configuration, and
troubleshooting techniques through practical hands-on examples with text and
image generation workflows. What I will be able to do after this course Build
generative AI applications using Amazon Bedrock APIs Configure prompts and
inference parameters for better AI outputs Integrate Amazon Q Developer with
Python and AWS workflows Generate text and images using leading foundation
models Troubleshoot model access, validation, timeout, and permission issues
Course Instructor(s) Karan Gupta is a DevOps Engineer, 4x AWS Certified
professional, and Certified Kubernetes Administrator. He has trained over
5,000 students and has extensive experience designing cloud-native
infrastructure, CI/CD pipelines, and AWS-based solutions for startups and
enterprises. He is also the author of more than 10 research papers focused on
technology-driven innovation. Who is it for This course is designed for Python
developers, AWS developers, cloud engineers, AI developers, and technical
professionals looking to build generative AI solutions on AWS. Basic
familiarity with Python, AWS services, and cloud computing concepts is
recommended, while prior machine learning experience is optional.
_ . __.
.. - - _//- ___\____---' [ R E C R U i T i N G ] . - _\_ ___--'-_ -- -_ .
iF YOU HAVE ANYTHiNG TO OFFER
CONTACT US ViA THE SCENE, OR EMAiL ADDRESS BELOW
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GREETiNGS TO ALL THE PAST AND PRESENT SCENE GROUPS AND SCENERS WHO MADE
STUF AVAiLABLE FOR THOSE THAT MAY NOT OTHERWISE HAD THE PRiViLEGE
_ _ _
.. -_- -/_- __--\__ [ C O N T A C T D E T A i L S ] --- -___-- - \ - .
lernstuf [at] proton [dot] me
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.. - - ___- _/ \____---' \\___-- .. - - ___- _/ \___---- -___-/__-- - -- .
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150M 001-Chapter_1_Introduction 6.2M 001-Chapter_1_Introduction/001-introduction.mkv 15M 001-Chapter_1_Introduction/002-bedrock.mkv 32M 001-Chapter_1_Introduction/003-bedrock_ui.mkv 18M 001-Chapter_1_Introduction/004-model_access_by_default_you_get_access_now.mkv 6.4M 001-Chapter_1_Introduction/005-post_model_access.mkv 29M 001-Chapter_1_Introduction/006-can_amazon_q_code.mkv 21M 001-Chapter_1_Introduction/007-chat_playground.mkv 15M 001-Chapter_1_Introduction/008-text_playground.mkv 11M 001-Chapter_1_Introduction/009-image_playground.mkv 67M 002-Chapter_2_Q_In_AWS_Lambda 11M 002-Chapter_2_Q_In_AWS_Lambda/010-q_developer.mkv 11M 002-Chapter_2_Q_In_AWS_Lambda/011-q_developer_benefits.mkv 14M 002-Chapter_2_Q_In_AWS_Lambda/012-using_amazon_q.mkv 32M 002-Chapter_2_Q_In_AWS_Lambda/013-can_we_ask_for_code_in_lambda_directly.mkv 257M 003-Chapter_3_Using_Code_With_Different_Models 9.3M 003-Chapter_3_Using_Code_With_Different_Models/014-using_q_in_lambda_with_bedrock.mkv 37M 003-Chapter_3_Using_Code_With_Different_Models/015-text_model_amazon_titan.mkv 41M 003-Chapter_3_Using_Code_With_Different_Models/016-text_model_claude.mkv 34M 003-Chapter_3_Using_Code_With_Different_Models/017-text_model_llama.mkv 23M 003-Chapter_3_Using_Code_With_Different_Models/018-troubleshoot_error.mkv 83M 003-Chapter_3_Using_Code_With_Different_Models/019-image_model_amazon_titan.mkv 32M 003-Chapter_3_Using_Code_With_Different_Models/020-image_model_stability_ai.mkv 92M 004-Chapter_4_Core_Concepts 20M 004-Chapter_4_Core_Concepts/021-ai.mkv 12M 004-Chapter_4_Core_Concepts/022-generative_ai_genai.mkv 11M 004-Chapter_4_Core_Concepts/023-genai_benefits.mkv 15M 004-Chapter_4_Core_Concepts/024-ai_genai_machine_learning_ml_and_deep_learning_dl.mkv 16M 004-Chapter_4_Core_Concepts/025-foundation_models_fm_vs_large_language_models_llm.mkv 14M 004-Chapter_4_Core_Concepts/026-prompt_engineering.mkv 6.9M 004-Chapter_4_Core_Concepts/027-types_of_prompt_engineering.mkv 361M 005-Chapter_5_Inference_Parameters 26M 005-Chapter_5_Inference_Parameters/028-inference_parameters.mkv 21M 005-Chapter_5_Inference_Parameters/029-temperature.mkv 26M 005-Chapter_5_Inference_Parameters/030-temperature_hands_on_i.mkv 26M 005-Chapter_5_Inference_Parameters/031-temperature_hands_on_ii.mkv 18M 005-Chapter_5_Inference_Parameters/032-top_p.mkv 33M 005-Chapter_5_Inference_Parameters/033-top_p_hands_on_i.mkv 36M 005-Chapter_5_Inference_Parameters/034-top_p_hands_on_ii.mkv 18M 005-Chapter_5_Inference_Parameters/035-top_k.mkv 28M 005-Chapter_5_Inference_Parameters/036-top_k_hands_on_i.mkv 22M 005-Chapter_5_Inference_Parameters/037-top_k_hands_on_ii.mkv 22M 005-Chapter_5_Inference_Parameters/038-most_probable_solution.mkv 14M 005-Chapter_5_Inference_Parameters/039-access_denied_error.mkv 21M 005-Chapter_5_Inference_Parameters/040-timeout_error.mkv 25M 005-Chapter_5_Inference_Parameters/041-validation_exception.mkv 31M 005-Chapter_5_Inference_Parameters/042-model_access_error.mkv 142M 006-Chapter_6_Additional_Configurations 19M 006-Chapter_6_Additional_Configurations/043-additional_configurations.mkv 15M 006-Chapter_6_Additional_Configurations/044-system_prompts.mkv 28M 006-Chapter_6_Additional_Configurations/045-code_for_system_prompts.mkv 11M 006-Chapter_6_Additional_Configurations/046-maximum_length.mkv 35M 006-Chapter_6_Additional_Configurations/047-code_for_maximum_length.mkv 12M 006-Chapter_6_Additional_Configurations/048-stop_sequence.mkv 26M 006-Chapter_6_Additional_Configurations/049-code_for_stop_sequence.mkv 652K LERNSTUF 648K LERNSTUF/lernstuf_introduction_2025.rar 1.1G total
File: 001-introduction.mkv Size: 6421423 bytes (6.12 MiB), duration: 00:01:19, avg.bitrate: 650 kb/s Audio: aac, 44100 Hz, stereo Video: h264, yuv420p, 1280x720, 30.00 fps(r) Subtitles: eng
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Keywords: Packt, Publishing, 8211, Amazon, Bedrock, And, Developer, For, Python, 2026, BOOKWARE, LERNSTUFDownload from Nitroflare
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