ML / Data Science

Batch: 2018/2019/2020/2021/2022/2023/2024. Requirements: - Strong knowledge of Python and libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn - Understanding of statistics, probability, linear algebra, and basic calculus - Knowledge of supervised and unsupervised machine learning - Understanding of algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, K-Means, and Gradient Boosting - Good understanding of data preprocessing, feature engineering, model evaluation, and cross-validation - Knowledge of SQL and relational databases - Familiarity with data visualization and exploratory data analysis - Strong problem-solving and analytical skills Preferred Skills: - Experience with Deep Learning using TensorFlow or PyTorch - Knowledge of NLP, Computer Vision, or Generative AI/LLMs - Familiarity with ML deployment and MLOps concepts - Experience with cloud platforms such as AWS, Azure, or GCP - Knowledge of Docker and APIs for deploying ML models - Experience working with large datasets and production ML systems