Generative Ai With Google – Bard, Palm Api And Google Cloud

Start your Generative AI journey today with Google Bard, PaLM API & Google Cloud Generative AI Studio

What you’ll learn
Understand the basics of Generative AI
Learn about the different types of Generative AI
Understand how Generative AI works
Apply Generative AI to real-world problems
Learn how to use Google’s Bard, PaLM API, and Google Cloud to create Generative AI content

Requirements
Some experience with programming

Description
I’m here to help you learn Generative AI Fundamentals!Do you think learning Generative AI is DIFFICULT? What if I can prove you WRONG?Learn Generative AI, AI and ML Fundamentals in a WEEKEND!Take your FIRST STEPS into the amazing world of Generative AI, Artificial Intelligence and Machine Learning using a HANDS-ON step by step approach.BEGINNERS to cloud, AI and ML are WELCOME!5 Things YOU need to know about this Generative AI Course#1: HANDS-ON – The best way to learn Generative AI Fundamentals is to get your hands dirty!#2: Designed for ABSOLUTE BEGINNERS #3: MULTI-CLOUD INSTRUCTOR – MORE THAN 100,000 Learners are learning AWS, Azure, and Google Cloud with us#4: FREE Downloadable PDF #5: 5 FREE Downloadable Python Notebook Examples Generative AI is the future of artificial intelligence. It is the ability of machines to create new content, such as images, text, and music, that is indistinguishable from human-created content. As this domain gains momentum, its potential applications are boundless. A number of developers think that understanding and making use of Generative AI needs in-depth knowledge of AI and ML. But guess what? That couldn’t be further from the truth! I’m Ranga Karanam. I’m the founder of in28minutes and creator of some of the worlds most popular courses on Cloud and DevOps. I’ve helped more than a million learners around the world acquire new tech skills. In this course, we will break down the misconception that Generative AI is difficult and guide you through the journey of embracing Generative AI with confidence. I’m a great believer that the best way to learn is by doing and we designed this course to be hands-on. You will play with a number of Generative AI services – Bard, PALM API, Generative AI Studio, MakerSuite and a lot more. You will also understand the fundamentals of AI, ML and how Generative AI fits into the AI/ML world. By the end of the course, you will NOT only understand how to become more productive using Generative AI but also understand how to make integrate Generative AI into your applications. While some programming knowledge is beneficial, no prior experience in generative AI is necessary.Are you ready to get started on the amazing journey to learn Generative AI with Google technologies?Do you want to join more than 1 MILLION learners having Amazing Learning Experiences with in28Minutes?Join Now!

Overview
Section 1: Introduction

Lecture 1 Generative AI with Google – Course Introduction

Lecture 2 DO NOT SKIP – Course Downloads

Section 2: Getting Started with Google Bard

Lecture 3 Step 01 What is Artificial Intelligence?

Lecture 4 Step 02 Playing with Bard – Getting Started

Lecture 5 Step 03 Playing with Bard – Coding, Learning and Design

Lecture 6 Step 04 Playing with Bard – Exploring Technology

Lecture 7 Step 05 Playing with Bard – Generating Ideas

Lecture 8 Step 06 Generative AI is NOT Deterministic

Section 3: Getting Started – AI vs ML vs Generative AI

Lecture 9 Step 01 Getting Started – AI vs ML vs Generative AI

Lecture 10 Step 02 Understanding Machine Learning vs Traditional Programming

Lecture 11 Step 03 Understanding Machine Learning Fundamentals – Features and Labels

Lecture 12 Step 04 Understanding Machine Learning Fundamentals – Steps and Terminology

Lecture 13 Step 05 The AI Turmoil – My View Point

Section 4: Exploring Generative AI Fundamentals

Lecture 14 Step 01 What is Generative AI?

Lecture 15 Step 02 Generative AI – Needs Huge Volumes of Data

Lecture 16 Step 03 Generative AI – Uses Self Supervised Learning

Lecture 17 Step 04 Key Step In Generative AI For Text – Predicting Next Word

Lecture 18 Step 05 Generative AI Text – Uses Tokens instead of Words

Lecture 19 Step 06 Exploring Predictive Machine Learning vs Generative AI

Section 5: ML in Google Cloud – An Overview

Lecture 20 Step 01 ML in Google Cloud – Traditional Landscape

Lecture 21 Step 02 ML in Google Cloud – 1 – Using Machine Learning API

Lecture 22 Step 03 ML in Google Cloud – 2 – Custom Models without ML expertise

Lecture 23 Step 04 ML in Google Cloud – 3 – Build Complex Custom Models

Lecture 24 Step 05 Creating GCP – Google Cloud Platform – Account

Lecture 25 Downloads – We will use the cloud images in Next Step

Lecture 26 Step 06 ML in Google Cloud – Quick Demo

Section 6: Generative AI with Google and Google Cloud – Quick Overview

Lecture 27 Step 01 Generative AI with Google and Google Cloud – Quick Overview

Lecture 28 Step 02 Exploring Generative AI Foundation Models

Lecture 29 Downloads – We will use generate ai studio – gen ai prompts file in next step

Lecture 30 Step 03 Exploring Text Features – Summarization

Lecture 31 Step 04 Exploring Text Features – Classification

Lecture 32 Step 05 Exploring Text Features – Extraction

Lecture 33 Step 06 Exploring Text Features – Ideation

Section 7: Getting Started with Prompt Design

Lecture 34 Step 01 Getting Started with Prompt Design

Lecture 35 Step 02 Giving Examples – ZERO SHOT vs ONE SHOT vs MANY SHOT

Lecture 36 Step 03 Exploring Prompt Frameworks – RTF, CTF and RASCEF

Lecture 37 Step 04 Experiment with Parameters

Section 8: Exploring Vertex AI PaLM API and Generative AI Studio Further

Lecture 38 Step 00 Executing Vertex AI PaLM API from Vertex AI Workbench

Lecture 39 Step 01 Exploring Vertex AI PaLM API – Text Model API

Lecture 40 Step 02 Exploring Chat Model

Lecture 41 Step 03 Exploring Code Models

Lecture 42 Step 04 Exploring Image Models

Lecture 43 Step 05 Exploring Speech Models

Lecture 44 Step 06 Cloud Best Practice – Stop Unused Resources – User Managed Notebook

Section 9: Exploring Generative AI Further

Lecture 45 Step 01 Tuning Language Models

Lecture 46 Step 02 What are Embeddings?

Lecture 47 Downloads – We will use generative ai studio notebooks in the next step

Lecture 48 Step 03 Exploring Embeddings with an Example

Lecture 49 Step 04 Getting Started with LangChain

Lecture 50 Step 05 Understanding LangChain Fundamentals

Lecture 51 Step 06 Exploring LangChain – Answering Questions from a Long Article

Lecture 52 Step 07 Exploring LangChain – Summarization

Lecture 53 Step 08 Executing Vertex AI – PaLM API From Colab

Section 10: Exploring Other Google Generative AI Offerings

Lecture 54 Step 00 Generative AI App Builder is NOT GA yet

Lecture 55 Step 01 Getting Started: Generative AI App Builder

Lecture 56 Step 02 00 MakerSuite and PaLM API are NOT GA yet

Lecture 57 Step 02 01 Getting Started: PaLM API and MakerSuite

Lecture 58 Step 03 Cloud Best Practice – Delete Unused Resources – User Managed Notebook

Section 11: Google AI Principles and Responsible AI practices

Lecture 59 Google AI Principles and Responsible AI practices

Section 12: Generative AI with Google – Congratulations

Lecture 60 Generative AI with Google – Congratulations

Lecture 61 Bonus Lecture

Anyone interested in learning about Generative AI