π How to Become an AI Engineer in 2026 π©π»βπ»Save for later
Step-by-step Roadmap
πΉ PHASE 1: Foundations (0β3 Months)
Donβt skip this. Weak foundations = stuck later.
1οΈβ£ Programming (Must-Have)
Python: loops, functions, OOP
Libraries: NumPy, Pandas, Matplotlib / Seaborn
π Practice daily:
LeetCode (easy)
HackerRank (Python)
2οΈβ£ Math for AI (Enough, not PhD level)
Focus only on:
Linear Algebra (vectors, matrices)
Probability & Statistics
Basic Calculus (idea of gradients)
π Conceptual understanding is enough β no heavy theory.
πΉ PHASE 2: Machine Learning (3β6 Months)
Learn:
Supervised & Unsupervised Learning
Feature Engineering
Model Evaluation
Algorithms:
Linear & Logistic Regression
KNN
Decision Trees
Random Forest
SVM
K-Means
Tools:
Scikit-learn
π Project Ideas:
House price prediction
Student performance prediction
Credit risk model
πΉ PHASE 3: Deep Learning & AI (6β10 Months)
Learn:
Neural Networks & Backpropagation
CNN (Images)
RNN / LSTM (Text)
Transformers (Basics)
Framewo...
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