Published 12/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.49 GB | Duration: 2h 3m
Learn to solve Real World Business Problems with Analytical Apps from an industry professional What you'll learn Solve Real World Business Problems with Analytical Apps Develop & Enhance your Data Analytics/Data Science portfolio Create a Solid Case to GET PROMOTED in Your Analytics Career Strengthen your Analytics Toolbox with DevOps Skills Requirements Basic Python experience Description Would you like to boost your IT career with the help of Analytics and Cloud Technology?You've come to the right place!There's no better way to achieve that than by solving a Real World Business Problem and sharing your solution with the audience in an interactive & web-accessible format!STREAMLIT has been helping me accomplish just that in IT, Food and Travel industries over the last 4 years.With the help of this amazing open-source framework I've drawn attention of C-level management to the areas for business improvement, grew my Team and even changed the country where I live & work!Streamlit has a really flat learning curve as it's 100% Python-based.At the same it enables you to go from an idea to a full-scale App running somewhere in the Internet in less than 1 day!Join me in this fun and Industry-shaped course to get new skills and improve your Tech&business acumen!By the end of this course you will be able to:Shape your ideas into a feasible Analytical App MVPPackage your ML models into Web Apps using STREAMLITDeploy your Apps to the Internet via Google CloudUpgrade your DS/DA toolbox by solid DevOps skillsAutomate App Cloud deployment via Gitlab CICD Overview Section 1: Intro Lecture 1 Welcome! Lecture 2 Course contents Lecture 3 Getting to know each other Lecture 4 Motivation to learn Streamlit Section 2: Fast kick-off Lecture 5 Launching an App locally in <5mins Lecture 6 App architecture & ML pipeline behind it Section 3: Solving Real World problem (Locally) Lecture 7 Defining the Business Problem Lecture 8 Industry workflow Lecture 9 Understanding the App Codebase Lecture 10 Packaging App into Docker Section 4: Upgrading the Solution (CLOUD) Lecture 11 Setting up GCP: part 1 Lecture 12 Setting up GCP: part 2 Lecture 13 Cloud deployment: part 1 Lecture 14 Cloud deployment: part 2 Section 5: Going PRO (Adding CI-CD) Lecture 15 Understanding the pipeline Lecture 16 Setting up GitLab Lecture 17 Deployment Lecture 18 Improvement ideas Section 6: Career Life Hacks Lecture 19 Ideas to Accelerate Your Career Python enthusiasts, Data Scientists, Data Analysts, Developers, AI professionals HomePage:
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