Women in AI: Building Skills, Confidence, and Careers through Open Source

[BTANISHA11]

Talk title

Women in AI: Building Skills, Confidence, and Careers through Open Source

Short talk description

Artificial Intelligence is shaping the future of technology, yet many women hesitate to step into AI roles due to unclear learning paths, lack of confidence, or limited access to real-world experience. This talk focuses on how open-source ecosystems can help bridge that gap.

The session explores how women can build strong AI fundamentals using Python and open-source tools, gain hands-on experience through real projects, and grow their careers by learning in public and engaging with tech communities. Alongside technical insights, the talk addresses confidence-building, visibility, and navigating common challenges faced by women in AI.

This session is ideal for beginners and early-career professionals looking to build sustainable and impactful AI careers.

Long talk description

Artificial Intelligence is no longer a niche skill, but for many women, entering the AI space still feels intimidating. Overwhelming learning resources, unclear expectations, and self-doubt often prevent capable individuals from taking the first step. This Women’s Day session is designed to make AI more approachable, practical, and inclusive.

The talk begins by breaking down what AI and Machine Learning look like in real-world practice, focusing on Python and widely used open-source libraries. Instead of emphasizing complex mathematics or abstract theory, the session highlights how AI practitioners actually work: exploring data, training models, evaluating results, and iterating through experimentation.

A core theme of the session is the power of open source. Contributing to open-source projects, participating in communities, and sharing work publicly can significantly accelerate learning while building credibility and confidence. The talk will discuss how beginners can start contributing — even without being “experts” — and how these contributions translate into real career opportunities.

Beyond technical skills, the session addresses confidence and career growth for women in AI. Topics include overcoming imposter syndrome, choosing learning paths intentionally, building a visible portfolio, and leveraging community support. Attendees will leave with a clear understanding of how to move from learning to impact, using open source as a foundation for long-term career growth.

This session is designed to be beginner-friendly, encouraging, and action-oriented, with practical takeaways that attendees can apply immediately.

What format do you have in mind?

BoF (Birds of a Feather) session (30-45 minutes, open discussion or topic exploration with the audience)

Talk outline / Agenda

Introduction & Women’s Day context (3 mins)

What AI and ML look like in practice (7 mins)

Python and open-source tools in AI workflows (5 mins)

Open source as a pathway to skills and credibility (5 mins)

Building confidence and visibility as a woman in AI (10 mins)

Resources, next steps & Q&A (10 mins)

Key takeaways

Clear understanding of AI and ML roles in real-world projects

Practical insight into Python and open-source tools used in AI

How open-source contributions support skill-building and confidence

Career growth strategies tailored for women in AI

Actionable next steps for learning and community involvement

What domain would you say your talk falls under?

Careers and Community

Duration (including Q&A)

30-45 min

Prerequisites and preparation

Basic familiarity with Python is helpful but not mandatory

No prior experience with AI or Machine Learning required

Suitable for students, beginners, and early-career professionals

No setup or installations required for attendees

Resources and references

Python official documentation

pandas, NumPy, scikit-learn documentation

Beginner-friendly AI and ML open-source projects

Articles and community resources focused on women in tech

GitHub repositories and contribution guides

Link to slides/demos (if available)

Will Share prior to the event.

Twitter/X handle (optional)

No response

LinkedIn profile (optional)

https://www.linkedin.com/in/tanishabansal110902/

Profile picture URL (optional)

No response

Speaker bio

I am a Software Engineer at SITA, working on building scalable systems with a strong focus on AI-driven solutions. I actively share content on technology, AI, and career growth, and enjoy breaking down complex topics into practical, easy-to-understand ideas.

I am a tech speaker, mentor, and hackathon judge, with experience supporting and reviewing 35+ hackathons and community initiatives. I am also an AWS Machine Learning community builder and have previously contributed to developer education as part of GeeksforGeeks.

I am passionate about open source, community learning, and supporting women in tech through mentorship and knowledge sharing. Through this talk, I aim to help attendees build skills, confidence, and clarity as they navigate AI careers using open-source ecosystems and community support.

Availability

Yes I am available on the specific date.

Accessibility & special requirements

No response

Speaker checklist

• I have read and understood the PyDelhi guidelines for submitting proposals and giving talks
• I will make my talk accessible to all attendees and will proactively ask for any accommodations or special requirements I might need
• I agree to share slides, code snippets, and other materials used during the talk with the community
• I will follow PyDelhi's Code of Conduct and maintain a welcoming, inclusive environment throughout my participation
• I understand that PyDelhi meetups are community-centric events focused on learning, knowledge sharing, and networking, and I will respect this ethos by not using this platform for self-promotion or hiring pitches during my presentation, unless explicitly invited to do so by means of a sponsorship or similar arrangement
• If the talk is recorded by the PyDelhi team, I grant permission to release the video on PyDelhi's YouTube channel under the CC-BY-4.0 license, or a different license of my choosing if I am specifying it in my proposal or with the materials I share

Additional comments

This is intended as a Women’s Day special session focused on encouragement, practical learning, and community support. I would welcome feedback, mentorship, or rehearsal opportunities if available.

[kirtivr]

Thanks for the talk proposal, Tanisha.

Could you please share the slides for your talk so the review can begin?

[BTANISHA11]

Yes sure

[BTANISHA11]

Yes sure

[kirtivr]

Upon further discussion with @satyaakam and @Daksh777 we think this talk would work very well in the following format:

1. The talk and ideas (15 - 20 min)
2. Open discussion among the audience OR Q&A (20 min) on certain topics like

"Insights and challenges while working on AI problems with Python"

"Career challenges faced by women"

"Contributing to Open Source"

Let us know if you think that would be a good idea.

[BTANISHA11]

https://www.canva.com/design/DAHBGMOkn_M/Oh1gzTtROXsL8TUktZBzHQ/edit?utm_content=DAHBGMOkn_M&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton
Here is the ppt link if any changes required do let me know @kirtivr

[BTANISHA11]

Upon further discussion with @satyaakam and @Daksh777 we think this talk would work very well in the following format:

1. The talk and ideas (15 - 20 min)
2. Open discussion among the audience OR Q&A (20 min) on certain topics like

"Insights and challenges while working on AI problems with Python"

"Career challenges faced by women"

"Contributing to Open Source"

Let us know if you think that would be a good idea.

Yeah I can do that way . Have included a bit of question and activities in between also can also modify as you said

[kirtivr]

Hey Tanisha, Thanks for sharing the presentation.

At PyDelhi we prefer deep dive type talks over overview type talks.

While your talk touches upon a very important topic, it doesn't really engage with it and doesn't provide much guidance.

In my opinion it will be difficult to get this talk to the level we want it to be.

Here is are some guidelines we have:

• when referring to ideas, refer to them by their technical definition.

This allows us to refer to case studies, and engage with the existing research that has been done on the topic.

For example : "Impostor Sydrome" over "I don't feel like I belong"

• When you mention a problem, also immediately discuss how to fix it. Keep the discussions open and allow anyone to contribute to the solution.

Here are some topics I think you can cover in the talk -

1. Combating societal bias -
   (a) Its considered good for men to be ambitious and prioritize their career, but not for women.

(b) Success and likeability are positively correlated for men and negatively correlated for women.

2. Priming effect ("men are better at math, women are better at social studies")- how can we fix this?

3. Impostor syndrome and how to get over it.

4. ⁠Lack of mentors for women because there are
   less women in tech. Would mentorship programs help?

Also sometimes it is a better investment to work on your own skills than to hope for a mentor.
Solving real business problems > anything else for career growth.

5. ⁠Career advise - Women tend to not go after high growth jobs at startups and unicorns, instead choosing more stable jobs. This leads to slower promotions and career progression.

I would encourage you to spend some more time and restructure the talk.

[BTANISHA11]

Yes sure . Will send updated presentationand topic by weekend. > Hey Tanisha, Thanks for sharing the presentation.

At PyDelhi we prefer deep dive type talks over overview type talks.

While your talk touches upon a very important topic, it doesn't really engage with it and doesn't provide much guidance.

In my opinion it will be difficult to get this talk to the level we want it to be.

Here is are some guidelines we have:

• when referring to ideas, refer to them by their technical definition.

This allows us to refer to case studies, and engage with the existing research that has been done on the topic.

For example : "Impostor Sydrome" over "I don't feel like I belong"

• When you mention a problem, also immediately discuss how to fix it. Keep the discussions open and allow anyone to contribute to the solution.

Here are some topics I think you can cover in the talk -

1. Combating societal bias -
   (a) Its considered good for men to be ambitious and prioritize their career, but not for women.

(b) Success and likeability are positively correlated for men and negatively correlated for women.

2. Priming effect ("men are better at math, women are better at social studies")- how can we fix this?

3. Impostor syndrome and how to get over it.

4. ⁠Lack of mentors for women because there are
   less women in tech. Would mentorship programs help?

Also sometimes it is a better investment to work on your own skills than to hope for a mentor.
Solving real business problems > anything else for career growth.

5. ⁠Career advise - Women tend to not go after high growth jobs at startups and unicorns, instead choosing more stable jobs. This leads to slower promotions and career progression.

I would encourage you to spend some more time and restructure the talk.

[kirtivr]

Awesome thanks!

I think we can keep certain topics as talking points for the open discussion.

For the remaining topics we want to present them somewhat in a problem & solution(s) format.