#. Proficient in Data Analysis via Python using steps - Data Cleaning, Data Transformation, EDA, Model Building, Validation, and Deployment.#. Have hands-on Experience with many algorithms such as Linear Regression, Logistic Regression, Random Forest, Decision Trees, SVM, XGBooster, PCA, and knowledge of CNN, ANN, RNN, NLP, and Computer Vision.#. Cloud Platform - AWS(EC2, ECR, S3 bucket)#. Core Py Libraries - Matplotlib, Seaborn, Pandas, Numpy, scikit-learn, Tensorflow, Keras#. Certified Data Scientist.