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Breaking Into AI/ML

Your comprehensive 8-week roadmap to transition into AI/ML. Three specialized tracks for Research, Applied ML, and MLOps careers.

Your Progress: Applied ML Track

0/8 weeks complete

Week-by-Week Learning Plan

Week 1

Python & Data Stack

NumPyPandasMatplotlib

Project: EDA on real dataset

Week 2

Classical ML

Scikit-learnFeature EngineeringModel Selection
Week 3

Deep Learning Basics

PyTorchKerasTraining Loops

Project: Image classifier

Week 4

NLP Fundamentals

TokenizationEmbeddingsSentiment Analysis
Week 5

LLM Applications

Prompt EngineeringRAGFine-tuning

Project: Build a chatbot

Week 6

Computer Vision

Object DetectionSegmentationVideo Analysis
Week 7

Production ML

FastAPIDockerModel Serving

Project: Deploy a model

Week 8

Portfolio Project

End-to-End MLDocumentation

Project: Complete ML application

Skills Translation Matrix

Your existing skills translate to AI/ML. Here's what to leverage and what to focus on:

From: Software Engineer

✓ Leverage These

CodingSystem Design

→ Focus On

MathML TheoryStatistics

From: Data Analyst

✓ Leverage These

SQLVisualizationBusiness Logic

→ Focus On

PythonDeep LearningEngineering

From: Academic Researcher

✓ Leverage These

MathResearchWriting

→ Focus On

EngineeringProduction MLDevOps

From: Product Manager

✓ Leverage These

CommunicationStrategy

→ Focus On

Technical DepthHands-on CodingML Intuition

From: Designer

✓ Leverage These

UXUser ResearchCreativity

→ Focus On

Technical SkillsData ThinkingML Applications

Recommended Certifications

CertificationProviderDifficultyValueTime
Google ML EngineerGoogle CloudIntermediate⭐⭐⭐⭐⭐3-6 months
AWS ML SpecialtyAmazonAdvanced⭐⭐⭐⭐⭐4-6 months
DeepLearning.AI SpecializationCourseraBeginner⭐⭐⭐⭐4-5 months
Fast.ai CourseFast.aiIntermediate⭐⭐⭐⭐⭐2-3 months
Hugging Face CertificationHugging FaceIntermediate⭐⭐⭐⭐1-2 months

Get the Complete PDF Roadmap

Includes detailed resources, project templates, and a printable checklist.

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