Data Science and AI using Python Training in USA

This course provides a thorough grounding in Data Science and Artificial Intelligence (AI) using Python. Participants will learn how to analyze, visualize, and model data, and apply machine learning algorithms to solve real-world problems. The course blends theoretical concepts with hands-on practice, covering everything from data preprocessing to deploying machine learning models.

Welcome to the official Data Science and AI using Python Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in USA. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic understanding of Python programming

• Fundamental knowledge of statistics and linear algebra is helpful

• Familiarity with Jupyter Notebooks and Python IDEs

• No prior experience in machine learning or AI is required

• Python for Data Science

• Data preprocessing and visualization

• Statistical analysis and hypothesis testing

• Supervised and unsupervised machine learning

• Deep learning with neural networks

• Model evaluation, optimization, and deployment

• Working with libraries: NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow/Keras

By the end of the course, participants will be able to:

• Understand the data science workflow and tools

• Use Python for data manipulation, visualization, and statistical analysis

• Build and evaluate machine learning models using Scikit-learn

• Apply AI techniques like deep learning using TensorFlow or PyTorch

• Handle real-world datasets and deliver actionable insights

• Deploy trained models using basic APIs or cloud platforms