Lilly Tech Systems
Resume & Portfolio for AI Careers
Your technical skills only matter if hiring managers see them. This course gives you the practical tools, templates, and strategies to build an AI career profile that gets noticed — from ATS-optimized resumes and GitHub portfolios to LinkedIn branding and targeted cover letters. Every lesson includes real examples, before/after comparisons, and actionable checklists you can use immediately.
Your Learning Path
Build your complete AI career package step by step — from resume fundamentals to application strategy.
1. Building Your AI Career Profile
What makes AI resumes different from general tech resumes, ATS optimization essentials, and what hiring managers at AI companies actually look for in candidates.
2. AI/ML Resume Writing
Resume structure and formatting, action verbs for ML work, quantifying ML impact with metrics, before/after examples, and role-specific templates for ML engineer, data scientist, and research scientist.
3. GitHub Portfolio Strategy
Which projects to showcase, README templates that impress, code quality signals reviewers check, documentation best practices, and pinned repos strategy.
4. Showcasing AI Projects
How to present ML projects effectively through blog posts, demo apps, Hugging Face Spaces, Streamlit demos, and Kaggle competitions that stand out.
5. LinkedIn & Personal Branding
Headline optimization for AI roles, About section templates, content posting strategy, networking tips, and building thought leadership in the AI community.
6. Cover Letters & Applications
AI-specific cover letter templates, cold outreach to hiring managers, referral strategy, application tracking systems, and targeting your applications effectively.
7. Checklist & Templates
Complete career package checklist, downloadable template descriptions, frequently asked questions accordion, and a comprehensive action plan for your AI job search.
What You'll Learn
By the end of this course, you will be able to:
Write an ATS-Optimized AI Resume
Craft a resume that passes automated screening systems, highlights your ML impact with quantified metrics, and matches the specific format hiring managers at AI companies expect.
Build a Compelling Portfolio
Create a GitHub portfolio with well-documented projects, professional READMEs, and clean code that demonstrates your technical depth and ability to ship real AI solutions.
Showcase Projects That Stand Out
Present your AI work through interactive demos, blog posts, and competition entries that show not just what you built, but how you think about ML problems.
Brand Yourself as an AI Professional
Develop a personal brand across LinkedIn and professional communities that attracts recruiters and builds your reputation as a serious AI practitioner.