The Ravit Show

Host of "The Ravit Show" I love to interview folks on my LinkedIn and YouTube Live. Anything and everything that's trending can be a topic on the show.

Founder and Host

Gartner

Gartner Ambassadors are active leaders who are eager to drive the discussion, share their knowledge, make new connections, and build their personal brand.

Gartner Ambassador

EM360

Board Advisor

AtScale

I look after social media, content, podcast production and community!

Head Community Evangelist

Story by Data

Affiliate Member

Open Data Science Conference (ODSC)

Packt

Senior Content Marketing Editor

As a Content Marketing Editor in the Expert Network team and look after content marketing materials produced by and for Expert Network authors and their titles. I am responsible for a portfolio of content marketing assets for each title, liaising with Producers, Technical Editors, and the wider EN team, and individual authors and technical reviewers as necessary. I am also responsible for liaising with other teams in the business to make appropriate marketing content available, on a title by title basis, as requirements arise, and sourcing further material where there are gaps.

- Create a repository of content marketing assets for each title, visible and available to other stakeholders
- Maintain and develop further content marketing assets as required in support of the individual title marketing for each EN author
- Ensure the completeness, accuracy, and availability of all promotional title information and materials for Expert Network titles.
- Create and maintain the Expert Network forthcoming catalogue to share with internal and external partners.
- Create, source, and curate content for the Outreach team, PTN team, Direct marketing team, and social channels.

Responsibilities:

I work with the Producer and Technical Editor of a title, and other team stakeholders, to pre-emptively produce or curate the following assets for each title across the lifecycle of the project:

- Content articles for the Hub and other partner channels in phases right from pre-pub to post-pub.
- Generate podcasts for authors to talk about the topic and promote the book.
- Providing a suggested social content plan across Expert Network titles, for integration and execution by the Packt social team
- An early pre-release extract, a “sneak preview” in the month before launch, and a highly shareable article immediately post-launch.
- An article based on an author interview with questions provided by the editor.
- The content and images for an Amazon A+ page, based on the author interview.

Content Marketing Editor

- Primary and secondary research on new development in the field of tech
- Getting insights from an industry expert on your projects to give an edge and value to your project making it unique
- Preparing questionnaires for the authors and the clients on our product line
- In-depth market forecasting and analysis of various sectors
- Creating roadmaps while working closely with multiple stakeholders on different projects in accordance with the TAT
- Prepared market engineering sheets at regular intervals that help you visualize complex data via MS Office Tools
- Internal and external stakeholder management including presentation to CXOs
- Understanding the business need, evaluating various processes and controls present in the organization, communicating control deficiencies and other issues encountered during the research process
- Keeping a tap on the commercial viability of the products

Associate Category Manager

S K Patodia & Associates

- Look after different domains of the business with accordance to the clients
- Managing team and preparing questionnaires for the training of research
- Handling accounts and budgets related to the projects
- In-depth primary research related to the projects
- Handling clients PAN India, while closely associating with internal stakeholders
- Forecast new areas in terms of commercial viability

Assistant Manager Research 

Hexa Research Pvt. Ltd.

- Prepare reports on different domains such as media, ICT, Chemical, Tech, FMCG and consumer insights
- Handling client reports while closely working with different internal and external stakeholders 
- To prepare reports with accordance with the client requirements from across the United States, Europe, APAC, Middle East
- Market forecasting considering the factors affecting the industries by Primary Research
- Understand the budget aspects as per the client's requirement
- Training the team and finishing the projects in given turn around time

Research Associate

Reliance Industries Limited

Working for Indirect Taxation on CENVAT credit input.

Finance Intern

Founder & Host of "The Ravit Show". I love to interview Data/AI Leaders on The Ravit Show. Hosted 500+ Data Science/AI leaders on The Ravit Show.

Ravit Jain is well known for --

- Hosting live events
- Data Community Building
- Community Evangelism
- Product Marketer
- Share free resources with Community
- Helping Data Science/AI Community

As the Founder & Host of The Ravit Show, my mission is to illuminate the intersection of media and technology by engaging with Data and AI leaders. With a focus on new business development and compelling communication, I've established a platform that resonates with industry professionals and enthusiasts alike.

I leverage my expertise in B2B influence to foster thought leadership and community building. Our team is dedicated to sharing knowledge, driving conversations, and creating meaningful connections within the tech community, with a special emphasis on the burgeoning fields of Data and AI.

You can reach out to me at Ravitjain0909@gmail.com for The Ravit Show queries :)

A clear path into AI engineering using 10 GitHub repos

Step-by-step plan you can follow and show as proof of work 

Foundations
	1.	Learn the basics of machine learning and deep learning
• ML for Beginners, AI for Beginners
Output: 3 small projects with short READMEs that explain the goal, data, and result.

Go deeper
2) Build neural nets from scratch
• Neural Networks: Zero to Hero
Output: a tiny GPT trained on a toy dataset, plus notes on what you changed and why.

Read papers in code
3) Study real architectures by walking through annotated implementations
• DL Paper Implementations
Output: pick one model and re-implement a minimal version. Write what you simplified.

Ship real software
4) Move from notebooks to apps and services
• Made With ML
Output: refactor one project with a simple API, tests, and a one-click run script.

Work with LLMs
5) Learn the core pieces end to end
• Hands-on LLMs
Output: a basic RAG app (retrieval augmented generation) that answers questions on a small knowledge base.

Make RAG better
6) Compare advanced techniques
• Advanced RAG Techniques
Output: run A/B tests on 3 settings and report latency, accuracy, and cost in a table.

Learn agents
7) Build simple agents that take steps toward a goal
• AI Agents for Beginners
Output: an agent that checks a site, writes a summary, and files a ticket.

Take agents toward production
8) Add memory, orchestration, and basic security
• Agents Towards Production
Output: logging, retry logic, and input checks. Note what fails and how you fixed it.

Round out your portfolio
9) Adapt working examples
• AI Engineering Hub
Output: 2 more apps that solve real tasks, each with a clear demo and setup guide.

How to pace this
• One repo per week is a good rhythm.
• Keep a single repo called “ai-engineering-journey” with subfolders per step.
• After each step, post a short write-up with a 30-second screen recording.

What hiring managers look for
• Working code that runs on first try.
• Clear README, data source, and limits.
• Small tests and a simple eval, even if manual.
• Changelog that shows steady progress.

Save this and start with step 1 today.

Repos and links
	1.	ML for Beginners — https://lnkd.in/dQ6nAJRC  
	2.	AI for Beginners — https://lnkd.in/dXwJJjMm  
	3.	Neural Networks: Zero to Hero — https://lnkd.in/dagQ3kmA  
	4.	DL Paper Implementations — https://lnkd.in/dyw54m73  
	5.	Made With ML — https://lnkd.in/duHjr2CY  
	6.	Hands-On Large Language Models — https://lnkd.in/dxEGzsgc  
	7.	Advanced RAG Techniques — https://lnkd.in/dd2TKA5P  
	8.	AI Agents for Beginners — https://lnkd.in/deznrHdf  
	9.	Agents Towards Production — https://lnkd.in/dz-WgU-3  
	10.	AI Engineering Hub — https://lnkd.in/d9cNqy7c

Ravit Jain

10 Github Repos for AI Engineering

🚨 Breaking News: Kestra 1.0 is here

On The Ravit Show, I sat down with Anna Geller and Will Russell from Kestra right as they unveiled Kestra 1.0, a release that could redefine orchestration for the enterprise.

Learn more -- https://go.kestra.io/ravit

Why this matters:

Why Kestra 1.0 is a gamechanger and has perfect timing? 

It’s a Long-Term Support (LTS) release built to unify data, AI, infrastructure, and business workflows under one orchestration engine. Teams can now:

- Cut automation costs by up to 40%
- Deploy in days instead of months
- Rely on full governance, audit trails, and approvals
- Move beyond fragmented schedulers like Airflow with clean migration paths

In my conversation with Anna and Will, we dug into:

- The headline features of 1.0
- What declarative agentic orchestration looks like in practice
- Where AI Agents shine — and where they don’t
- How Kestra balances automation with trust and control
- Why this release gives enterprises a stable backbone to build on

Love the product announcements here. It’s a statement that orchestration can be reliable, scalable, and ready for the AI-driven enterprise era.

👉 Full Kestra 1.0 announcement here: https://go.kestra.io/ravit

👉 Watch my interview with Anna and Will where we unpack what this means for data, AI, and infra teams.

The orchestration race just changed gears.

#data #ai #orchestration #kestra #theravitshow

🚨 Breaking News in Orchestration! Kestra has officially launched Kestra 1.0, and this is a release that changes the game.

Why it matters: Most orchestration tools were built for a different era, fragmented schedulers, siloed workflows, and endless custom fixes. With Kestra 1.0, we now have an enterprise-grade, Long-Term Support (LTS) release that unifies data, AI, infrastructure, and business workflows under one platform.

Highlights of Kestra 1.0:

- 40% cost savings on automation
- Deploy in days, not months
- Full approvals, audit trails, and role-based governance
- Clear migration path from Airflow and custom schedulers

Declarative agentic orchestration, bringing AI into workflows while keeping control intact!

I had the chance to speak with Anna Geller and Will Russell from Kestra right as this announcement went live on The Ravit Show. We dug into:

- What makes 1.0 different from anything else in orchestration
- How agentic orchestration really works in practice
- The balance between AI-driven automation and enterprise trust

Why Kestra believes this release sets a new standard for the orchestration's future

👉 Watch the full conversation here: Kestra 1.0 Launch Interview -- https://lnkd.in/dv723_wx

👉 Full announcement: Kestra Blog -- 👉 https://go.kestra.io/ravit

This isn’t just another product release — it’s a new foundation for how enterprises can scale orchestration in the AI era!

#data #ai #kestra #theravitshow

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