{"id":19948,"date":"2024-03-06T12:55:32","date_gmt":"2024-03-06T12:55:32","guid":{"rendered":"https:\/\/stage.cloudthat.com\/training\/?post_type=stm-courses&p=19948"},"modified":"2025-03-19T07:42:29","modified_gmt":"2025-03-19T07:42:29","slug":"amazon-sagemaker-studio-for-data-scientists","status":"publish","type":"stm-courses","link":"https:\/\/stage.cloudthat.com\/training\/aws\/amazon-sagemaker-studio-for-data-scientists","title":{"rendered":"Amazon SageMaker Studio for Data Scientists"},"content":{"rendered":"

This course covers the following topics:<\/p>\n

Introduction to Amazon SageMaker Studio<\/strong>: An overview of SageMaker Studio’s features, including its integrated Jupyter notebooks, model debugging, and experimentation tools.<\/p>\n

Data Preprocessing<\/strong>: Techniques for preparing and cleaning datasets for training and inference.<\/p>\n

Model Building and Training<\/strong>: How to build and train machine learning models using SageMaker’s built-in algorithms and AutoML capabilities.<\/p>\n

Model Deployment and Monitoring<\/strong>: Deploying models to SageMaker endpoints and monitoring their performance.<\/p>\n

Continuous Integration\/Continuous Deployment (CI\/CD) Pipelines<\/strong>: Automating the process of deploying and updating models in production.<\/p>\n","protected":false},"excerpt":{"rendered":"

This course covers the following topics: Introduction to Amazon SageMaker Studio: An overview of SageMaker Studio’s features, including its integrated Jupyter notebooks, model debugging, and experimentation tools. Data Preprocessing: Techniques for preparing and cleaning datasets for training and inference. Model Building and Training: How to build and train machine learning models using SageMaker’s built-in algorithms […]<\/p>\n","protected":false},"author":13,"featured_media":13808,"template":"","meta":{"footnotes":""},"stm_lms_course_taxonomy":[59],"metadata":{"stm_lms_product_id":["19949"],"_edit_lock":["1742370047:2"],"_edit_last":["2"],"permalink_customizer":["aws\/amazon-sagemaker-studio-for-data-scientists"],"permalink_customizer_regenerate_status":["1"],"_wp_page_template":["default"],"price":["34900"],"wpdocs-meta-bdt":["39900"],"wpdocs-meta-gbp":["1399"],"wpdocs-meta-usd":["1599"],"_yoast_wpseo_estimated-reading-time-minutes":["1"],"_yoast_wpseo_wordproof_timestamp":[""],"popular_course":["0"],"_popular_course":["field_64253688bc2e5"],"educational_schema":[""],"_educational_schema":["field_652fbbf6f589a"],"course_banner_image":[""],"_course_banner_image":["field_63c69a6b81cf1"],"mobile_banner_image":[""],"_mobile_banner_image":["field_63cf93896d207"],"banner_link":[""],"_banner_link":["field_63c69a9681cf2"],"banner_image":[""],"_banner_image":["field_621873548f922"],"banner_description":["Amazon SageMaker Studio for Data Scientists\" is a course designed to provide data scientists with an in-depth understanding of Amazon SageMaker Studio, a fully-integrated development environment for machine learning (ML). SageMaker Studio allows data scientists to build, train, deploy, and monitor machine learning models at scale, all within a single interface"],"_banner_description":["field_612c733ed3564"],"overview_section_heading":["Course Overview:"],"_overview_section_heading":["field_64538867ffdd0"],"after_completing_course_heading":["After completing this course, students will be able to:"],"_after_completing_course_heading":["field_645c78ade3f50"],"after_completing_course":["6"],"_after_completing_course":["field_6103aae828228"],"key_features_heading":["Key Features:"],"_key_features_heading":["field_645388ceffdd1"],"key_features":["5"],"_key_features":["field_6103aaff28229"],"who_should_attend_heading":["Who Should Attend:"],"_who_should_attend_heading":["field_645388faffdd2"],"who_should_attend":["3"],"_who_should_attend":["field_6103ab0d2822a"],"prerequisites_heading":["Prerequisites:"],"_prerequisites_heading":["field_64538a51ffdd3"],"prerequisites_text":["

  • AWS Technical Essentials (1\u2013day AWS instructor led course) <\/li>\r\n

    We recommend students who are not experienced data scientists complete the following two courses followed by 1-year on-the-job experience building models prior to taking this course:<\/P>\r\n

  • The Machine Learning Pipeline on AWS (4\u2013day AWS instructor led course) <\/li>\r\n
  • Deep Learning on AWS (1\u2013day AWS instructor led course) <\/li>"],"_prerequisites_text":["field_612c7498c4b84"],"question_sets_details_heading":[""],"_question_sets_details_heading":["field_65d303841f38d"],"question_sets_details_description":[""],"_question_sets_details_description":["field_65d303841f38e"],"question_sets_details_button_text":[""],"_question_sets_details_button_text":["field_65d303841f38f"],"question_sets_details_question_sets":[""],"_question_sets_details_question_sets":["field_65d303841f390"],"question_sets_details":[""],"_question_sets_details":["field_65d303841f38c"],"category_features_heading":[""],"_category_features_heading":["field_644b8ff35049c"],"category_features_features":[""],"_category_features_features":["field_644b90025049d"],"category_features_cta_text":[""],"_category_features_cta_text":["field_644b90285049f"],"category_features_cta_link":[""],"_category_features_cta_link":["field_644b902d504a0"],"category_features":[""],"_category_features":["field_644b8fe15049b"],"course_features_0_heading":["Learning objective of the course:"],"_course_features_0_heading":["field_644a0fae0e67e"],"course_features_0_features_list":["7"],"_course_features_0_features_list":["field_644a0fb70e67f"],"course_features_0_background_color":["a:1:{i:0;s:4:\"blue\";}"],"_course_features_0_background_color":["field_644a0fde0e681"],"course_features":["1"],"_course_features":["field_644a0fa10e67d"],"certification_heading":["Certification details:"],"_certification_heading":["field_64538bffffdd5"],"certification":["1"],"_certification":["field_6103ab1a2822b"],"about_trainer":[""],"_about_trainer":["field_6103ab6c2822f"],"course_fee_heading":[""],"_course_fee_heading":["field_64538c1cffdd6"],"course_fee_list":[""],"_course_fee_list":["field_6103abb728234"],"brochure_pdf":["21629"],"_brochure_pdf":["field_61232e258f89b"],"trainer":[""],"_trainer":["field_6124990e13784"],"course_outline_heading":["Course Outline:"],"_course_outline_heading":["field_64538a8effdd4"],"course_section":["6"],"_course_section":["field_612f4f27b0276"],"note_section":[""],"_note_section":["field_616d3ed46bbd2"],"popular_sort":[""],"_popular_sort":["field_6172496402af3"],"related_courses":["a:3:{i:0;s:4:\"8540\";i:1;s:4:\"8558\";i:2;s:5:\"20031\";}"],"_related_courses":["field_61c453ca6b2dd"],"reviews_heading":[""],"_reviews_heading":["field_64538c39ffdd7"],"review_rating":[""],"_review_rating":["field_62a813a92bee6"],"total_review_count":["2772"],"_total_review_count":["field_62b002d8d2de5"],"average_review_count":["4.5"],"_average_review_count":["field_62b00367d2de6"],"faq_heading":[""],"_faq_heading":["field_64538c59ffdd8"],"curriculum":[""],"featured":[""],"views":["2658"],"level":["advanced"],"current_students":["0"],"duration_info":["3 Days"],"video_duration":[""],"status":[""],"status_dates":[""],"not_single_sale":[""],"sale_price":[""],"sale_price_dates":[""],"enterprise_price":[""],"not_membership":[""],"affiliate_course":[""],"affiliate_course_text":[""],"affiliate_course_link":[""],"expiration_course":[""],"end_time":[""],"drip_content":[""],"prerequisites":[""],"prerequisite_passing_level":[""],"announcement":[""],"faq":[""],"course_files_pack":[""],"course_certificate":[""],"type":[""],"video_type":[""],"presto_player_idx":[""],"lesson_video":[""],"lesson_video_poster":[""],"lesson_video_width":[""],"lesson_shortcode":[""],"lesson_embed_ctx":[""],"lesson_youtube_url":[""],"lesson_stream_url":[""],"lesson_vimeo_url":[""],"lesson_ext_link_url":[""],"duration":[""],"preview":[""],"lesson_excerpt":[""],"lesson_files_pack":[""],"questions":[""],"quiz_style":[""],"duration_measure":[""],"correct_answer":[""],"passing_grade":[""],"re_take_cut":[""],"random_questions":[""],"answers":[""],"question_explanation":[""],"question_view_type":[""],"review_course":[""],"review_user":[""],"review_mark":[""],"order":[""],"absolute":[""],"sticky":[""],"sticky_threshold":[""],"sticky_threshold_color":[""],"stm_agenda":[""],"stm_host":[""],"stm_select_approved_denied":[""],"stm_multiselect_approved":[""],"stm_multiselect_denied":[""],"stm_date":[""],"stm_time":[""],"stm_timezone":[""],"stm_duration":[""],"stm_password":[""],"stm_waiting_room":[""],"stm_join_before_host":[""],"stm_host_join_start":[""],"stm_start_after_participants":[""],"stm_mute_participants":[""],"stm_enforce_login":[""],"stm_alternative_hosts":[""],"author_id":[""],"emails":[""],"sale_price_dates_start":[""],"sale_price_dates_end":[""],"_yoast_wpseo_primary_stm_lms_course_taxonomy":["59"],"after_completing_course_0_desciption":["Use Amazon SageMaker Studio IDE to develop, train, and deploy machine learning models."],"_after_completing_course_0_desciption":["field_6103ad2f9f5b2"],"after_completing_course_1_desciption":["Prepare and clean datasets for training and inference."],"_after_completing_course_1_desciption":["field_6103ad2f9f5b2"],"after_completing_course_2_desciption":["Build and train models with SageMaker's algorithms and AutoML capabilities."],"_after_completing_course_2_desciption":["field_6103ad2f9f5b2"],"after_completing_course_3_desciption":["Deploy models to SageMaker endpoints and monitor performance."],"_after_completing_course_3_desciption":["field_6103ad2f9f5b2"],"after_completing_course_4_desciption":["Automate model deployment with CI\/CD pipelines."],"_after_completing_course_4_desciption":["field_6103ad2f9f5b2"],"after_completing_course_5_desciption":["Debug and experiment with models for improved performance."],"_after_completing_course_5_desciption":["field_6103ad2f9f5b2"],"key_features_0_lists":["Hands-on labs for real-world application."],"_key_features_0_lists":["field_6103ad559f5b3"],"key_features_1_lists":["A comprehensive curriculum that covers all aspects of using SageMaker Studio."],"_key_features_1_lists":["field_6103ad559f5b3"],"key_features_2_lists":["Instruction from expert instructors."],"_key_features_2_lists":["field_6103ad559f5b3"],"key_features_3_lists":["A flexible schedule with online and in-person options."],"_key_features_3_lists":["field_6103ad559f5b3"],"key_features_4_lists":["A certification upon completion."],"_key_features_4_lists":["field_6103ad559f5b3"],"who_should_attend_0_attend_lists":["Data scientists and machine learning practitioners"],"_who_should_attend_0_attend_lists":["field_6103adfb3f3e4"],"who_should_attend_1_attend_lists":["Professionals interested in Amazon SageMaker and AWS tools"],"_who_should_attend_1_attend_lists":["field_6103adfb3f3e4"],"who_should_attend_2_attend_lists":["Individuals looking to enhance their data science skills."],"_who_should_attend_2_attend_lists":["field_6103adfb3f3e4"],"course_features_0_features_list_0_list":["Understand the key concepts of data science and machine learning."],"_course_features_0_features_list_0_list":["field_644a0fc80e680"],"course_features_0_features_list_1_list":["Use Amazon SageMaker Studio for data exploration, model development, and model deployment."],"_course_features_0_features_list_1_list":["field_644a0fc80e680"],"course_features_0_features_list_2_list":["Train and evaluate machine learning models using SageMaker algorithms and AutoML."],"_course_features_0_features_list_2_list":["field_644a0fc80e680"],"course_features_0_features_list_3_list":["Deploy machine learning models to SageMaker endpoints for inference."],"_course_features_0_features_list_3_list":["field_644a0fc80e680"],"course_features_0_features_list_4_list":["Monitor model performance using SageMaker's built-in monitoring tools."],"_course_features_0_features_list_4_list":["field_644a0fc80e680"],"course_features_0_features_list_5_list":["Set up CI\/CD pipelines to automate model deployment and updating."],"_course_features_0_features_list_5_list":["field_644a0fc80e680"],"course_features_0_features_list_6_list":["Debug and experiment with models for improved performance."],"_course_features_0_features_list_6_list":["field_644a0fc80e680"],"certification_0_short_description":[""],"_certification_0_short_description":["field_6103ab2f2822c"],"certification_0_list_content":[""],"_certification_0_list_content":["field_6103ab4a2822d"],"certification_0_image":["17714"],"_certification_0_image":["field_6103ab5b2822e"],"course_section_0_module_title":["Amazon SageMaker Studio Setup"],"_course_section_0_module_title":["field_612f5535940c3"],"course_section_0_module_description":[""],"_course_section_0_module_description":["field_612f564c921af"],"course_section_0_section_0_title":[""],"_course_section_0_section_0_title":["field_612f5233b0278"],"course_section_0_section_0_lesson_list_0_lession_title":["JupyterLab Extensions in SageMaker Studio"],"_course_section_0_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_0_section_0_lesson_list_1_lession_title":["Demonstration: SageMaker user interface demo"],"_course_section_0_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_0_section_0_lesson_list":["2"],"_course_section_0_section_0_lesson_list":["field_612f530a0ac40"],"course_section_0_section":["1"],"_course_section_0_section":["field_612f51e6b0277"],"course_section_1_module_title":["Data Processing"],"_course_section_1_module_title":["field_612f5535940c3"],"course_section_1_module_description":[""],"_course_section_1_module_description":["field_612f564c921af"],"course_section_1_section_0_title":[""],"_course_section_1_section_0_title":["field_612f5233b0278"],"course_section_1_section_0_lesson_list_0_lession_title":["Using SageMaker Data Wrangler for data processing"],"_course_section_1_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_1_lession_title":["Hands-On Lab: Analyze and prepare data using Amazon SageMaker Data Wrangler"],"_course_section_1_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_2_lession_title":["Using Amazon EMR"],"_course_section_1_section_0_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_3_lession_title":["Hands-On Lab: Analyze and prepare data at scale using Amazon EMR"],"_course_section_1_section_0_lesson_list_3_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_4_lession_title":["Using AWS Glue interactive sessions"],"_course_section_1_section_0_lesson_list_4_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_5_lession_title":["Using SageMaker Processing with custom scripts"],"_course_section_1_section_0_lesson_list_5_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_6_lession_title":["Hands-On Lab: Data processing using Amazon SageMaker Processing and SageMaker Python SDK"],"_course_section_1_section_0_lesson_list_6_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_7_lession_title":["SageMaker Feature Store"],"_course_section_1_section_0_lesson_list_7_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list_8_lession_title":["Hands-On Lab: Feature engineering using SageMaker Feature Store"],"_course_section_1_section_0_lesson_list_8_lession_title":["field_612f533b0ac41"],"course_section_1_section_0_lesson_list":["9"],"_course_section_1_section_0_lesson_list":["field_612f530a0ac40"],"course_section_1_section":["1"],"_course_section_1_section":["field_612f51e6b0277"],"course_section_2_module_title":["Model Development"],"_course_section_2_module_title":["field_612f5535940c3"],"course_section_2_module_description":[""],"_course_section_2_module_description":["field_612f564c921af"],"course_section_2_section_0_title":[""],"_course_section_2_section_0_title":["field_612f5233b0278"],"course_section_2_section_0_lesson_list_0_lession_title":["SageMaker training jobs"],"_course_section_2_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list_1_lession_title":["Built-in algorithms"],"_course_section_2_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list_2_lession_title":["Bring your own script"],"_course_section_2_section_0_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list_3_lession_title":["Bring your own container"],"_course_section_2_section_0_lesson_list_3_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list_4_lession_title":["SageMaker Experiments"],"_course_section_2_section_0_lesson_list_4_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list_5_lession_title":["Hands-On Lab: Using SageMaker Experiments to Track Iterations of Training and Tuning Models"],"_course_section_2_section_0_lesson_list_5_lession_title":["field_612f533b0ac41"],"course_section_2_section_0_lesson_list":["6"],"_course_section_2_section_0_lesson_list":["field_612f530a0ac40"],"course_section_2_section_1_title":[""],"_course_section_2_section_1_title":["field_612f5233b0278"],"course_section_2_section_1_lesson_list_0_lession_title":["SageMaker Debugger"],"_course_section_2_section_1_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_1_lession_title":["Hands-On Lab: Analyzing, Detecting, and Setting Alerts Using SageMaker Debugger"],"_course_section_2_section_1_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_2_lession_title":["Automatic model tuning"],"_course_section_2_section_1_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_3_lession_title":["SageMaker Autopilot: Automated ML"],"_course_section_2_section_1_lesson_list_3_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_4_lession_title":["Demonstration: SageMaker Autopilot"],"_course_section_2_section_1_lesson_list_4_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_5_lession_title":["Bias detection"],"_course_section_2_section_1_lesson_list_5_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_6_lession_title":["Hands-On Lab: Using SageMaker Clarify for Bias and Explainability"],"_course_section_2_section_1_lesson_list_6_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list_7_lession_title":["SageMaker Jumpstart"],"_course_section_2_section_1_lesson_list_7_lession_title":["field_612f533b0ac41"],"course_section_2_section_1_lesson_list":["8"],"_course_section_2_section_1_lesson_list":["field_612f530a0ac40"],"course_section_2_section":["2"],"_course_section_2_section":["field_612f51e6b0277"],"course_section_3_module_title":["Deployment and Inference"],"_course_section_3_module_title":["field_612f5535940c3"],"course_section_3_module_description":[""],"_course_section_3_module_description":["field_612f564c921af"],"course_section_3_section_0_title":[""],"_course_section_3_section_0_title":["field_612f5233b0278"],"course_section_3_section_0_lesson_list_0_lession_title":["SageMaker Model Registry"],"_course_section_3_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_1_lession_title":["SageMaker Pipelines"],"_course_section_3_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_2_lession_title":["Hands-On Lab: Using SageMaker Pipelines and SageMaker Model Registry with SageMaker Studio"],"_course_section_3_section_0_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_3_lession_title":["SageMaker model inference options"],"_course_section_3_section_0_lesson_list_3_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_4_lession_title":["Amazon SageMaker Studio for Data Scientists"],"_course_section_3_section_0_lesson_list_4_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_5_lession_title":["Testing strategies, performance, and optimization"],"_course_section_3_section_0_lesson_list_5_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list_6_lession_title":["Hands-On Lab: Inferencing with SageMaker Studio"],"_course_section_3_section_0_lesson_list_6_lession_title":["field_612f533b0ac41"],"course_section_3_section_0_lesson_list":["7"],"_course_section_3_section_0_lesson_list":["field_612f530a0ac40"],"course_section_3_section":["1"],"_course_section_3_section":["field_612f51e6b0277"],"course_section_4_module_title":["Monitoring"],"_course_section_4_module_title":["field_612f5535940c3"],"course_section_4_module_description":[""],"_course_section_4_module_description":["field_612f564c921af"],"course_section_4_section_0_title":[""],"_course_section_4_section_0_title":["field_612f5233b0278"],"course_section_4_section_0_lesson_list_0_lession_title":["Amazon SageMaker Model Monitor"],"_course_section_4_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_4_section_0_lesson_list_1_lession_title":["Discussion: Case study"],"_course_section_4_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_4_section_0_lesson_list_2_lession_title":["Demonstration: Model Monitoring"],"_course_section_4_section_0_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_4_section_0_lesson_list":["3"],"_course_section_4_section_0_lesson_list":["field_612f530a0ac40"],"course_section_4_section":["1"],"_course_section_4_section":["field_612f51e6b0277"],"course_section_5_module_title":["Managing SageMaker Studio Resources and Updates"],"_course_section_5_module_title":["field_612f5535940c3"],"course_section_5_module_description":[""],"_course_section_5_module_description":["field_612f564c921af"],"course_section_5_section_0_title":[""],"_course_section_5_section_0_title":["field_612f5233b0278"],"course_section_5_section_0_lesson_list_0_lession_title":["Accrued cost and shutting down"],"_course_section_5_section_0_lesson_list_0_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_1_lession_title":["Updates"],"_course_section_5_section_0_lesson_list_1_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_2_lession_title":["Capstone"],"_course_section_5_section_0_lesson_list_2_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_3_lession_title":["Environment setup"],"_course_section_5_section_0_lesson_list_3_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_4_lession_title":["Challenge 1: Analyze and prepare the dataset with SageMaker Data Wrangler"],"_course_section_5_section_0_lesson_list_4_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_5_lession_title":["Challenge 2: Create feature groups in SageMaker Feature Store"],"_course_section_5_section_0_lesson_list_5_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_6_lession_title":["Challenge 3: Perform and manage model training and tuning using SageMaker Experiments"],"_course_section_5_section_0_lesson_list_6_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_7_lession_title":["Challenge 4: Use SageMaker Debugger for training performance and model optimization"],"_course_section_5_section_0_lesson_list_7_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_8_lession_title":["Challenge 5: Evaluate the model for bias using SageMaker Clarify"],"_course_section_5_section_0_lesson_list_8_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_9_lession_title":["Challenge 6: Perform batch predictions using model endpoint"],"_course_section_5_section_0_lesson_list_9_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list_10_lession_title":["Challenge 7: Automate full model development process using SageMaker Pipeline"],"_course_section_5_section_0_lesson_list_10_lession_title":["field_612f533b0ac41"],"course_section_5_section_0_lesson_list":["11"],"_course_section_5_section_0_lesson_list":["field_612f530a0ac40"],"course_section_5_section":["1"],"_course_section_5_section":["field_612f51e6b0277"],"_yoast_wpseo_title":["Master Amazon SageMaker Studio: Streamline Your Data Science Workflow"],"_yoast_wpseo_metadesc":["Unveil the power of Amazon SageMaker Studio! This guide equips data scientists with the knowledge to navigate the collaborative and efficient environment, enabling them to build, train, and deploy machine learning models seamlessly."],"_wp_old_date":["2024-03-01"],"_thumbnail_id":["13808"],"_yoast_wpseo_canonical":["https:\/\/stage.cloudthat.com\/training\/aws\/amazon-sagemaker-studio-for-data-scientists"],"_regular_price_wmcp":["{\"USD\":\"1599\",\"GBP\":\"1399\",\"BDT\":\"39900\"}"],"_yoast_wpseo_content_score":["90"]},"acf":[],"_links":{"self":[{"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/stm-courses\/19948"}],"collection":[{"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/stm-courses"}],"about":[{"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/types\/stm-courses"}],"author":[{"embeddable":true,"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/users\/13"}],"version-history":[{"count":0,"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/stm-courses\/19948\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/media\/13808"}],"wp:attachment":[{"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/media?parent=19948"}],"wp:term":[{"taxonomy":"stm_lms_course_taxonomy","embeddable":true,"href":"https:\/\/stage.cloudthat.com\/training\/wp-json\/wp\/v2\/stm_lms_course_taxonomy?post=19948"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}