Nokia is Hiring for Data Scientist for the Automation Team for Noida location, interested candidates can share their resume at vikas.15.sharma@nokia.com.

Role - Data Science Associate.
Experience - 2-4 Yrs
Skills - Python, Machine Learning, Natural Language Processing etc.
Location - Noida(Hybrid).

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If tomorrow I were hit by a bus, got a concussion, and lost all of my memory.
I would be SAD, but I'd still want to learn ML engineering from scratch. And here is how I would do it in 2024, mostly in order:

Learn math:
- linear algebra: Matrices, vectors, linear equations and transformations,
- probability and statistics: Distributions, hypothesis testing, Bias-Variance Tradeoff, and conditional probability.
- calculus: Derivatives, integrals, gradient descent.

Learn Python:
- data structures: Lists, arrays, and dictionaries.
- libraries: NumPy, Pandas for data manipulations, scikit-learn for ml and Matplotlib for data viz.
- code organization and control flow: Functions, loops, and conditionals.

Data Preprocessing:
- learn how to handle missing values, duplicates, and outliers
- read on feature engineering
- try out data normalization and scaling

Core ML Algorithms:
- Supervised Learning: Linear and Logistic Regression, and Classification algorithms(K-NN, Decision Trees, SVM)
- Unsupervised Learning: Clustering (K-means) and dimensionality reduction techniques (PCA)
- Reinforcement Learning: Basics of agents, environments, and reward systems

Model Evaluation and Validation:
- learn metrics like accuracy, precision, recall, and F1 score
- cross-validation techniques
- learn about overfitting and underfitting, and how to address them

Get Hands-On Experience with Deployment:
- use datasets from Kaggle and/or models from Huggingface.
- learn to deploy with Flask, FastAPI, and on Cloud (AWS or Azure or GCP)
- participate in ml competitions or workshops.

Digest everything before diving into advanced topics like:
- ml frameworks like PyTorch, and TensorFlow
- neural networks, convolutional networks, and recurrent networks
- understand (NLP) and computer vision (CV) applications and ensemble techniques