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In this program, the participant will be responsible for learning and applying machine learning (ML) and artificial intelligence (AI) principles using Python and modern data science tools. The program emphasizes both theoretical understanding and applied implementation of ML algorithms, data processing, visualization, and model evaluation. Participants will gain hands-on experience building, testing, and deploying models using industry-standard frameworks and workflows.The training also introduces essential software engineering concepts, including version control, CI/CD automation, and Docker-based MLOps practices to ensure participants are prepared to operate in collaborative, production-grade ML environments.The instructional mode will be comprised of hands-on demonstration provided by company subject matter experts, along with some online or computer based training.
Jobs this program prepares you for
Design, develop, and evaluate data-driven solutions using Python, statistical methods, and machine learning frameworks. Collect, clean, and transform structured and unstructured data for analysis and model development. Apply classical ML algorithms and deep learning techniques for predictive modeling, computer vision, and natural language processing tasks. Develop scripts, pipelines, and notebooks for experimentation, model training, and data visualization. Collaborate in Agile teams using GitLab for version control, code review, and CI/CD integration. Implement experiment tracking, hyperparameter tuning, and result analysis using Weights & Biases (W&B). Build and containerize reproducible ML workflows using Docker and GitLab CI pipelines.
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