Data Science and Artificial Intelligence with Python

About this course

This course contains the use of artificial intelligence.

Step into the world of Data Science, Artificial Intelligence (AI), and Machine Learning (ML) with Python through this comprehensive foundation course designed to help learners build essential knowledge and practical skills in these rapidly growing fields.

The course begins with the fundamentals of Data Science, including the role of a Data Scientist, the Data Science pipeline, commonly used tools, and practical environments such as Anaconda, Jupyter Notebook, PyPI, and Pip. Learners will also explore real-world applications and case studies to understand how Data Science is used across different industries.

You will develop an understanding of important mathematical, statistical, and probability concepts required for Data Science and AI/ML. The course then introduces NumPy and Pandas, enabling you to work with arrays, datasets, DataFrames, data manipulation, querying, sorting, grouping, aggregation, and data from multiple sources.

As you progress, you will learn essential data preprocessing and exploratory data analysis (EDA) techniques, including handling missing values, selecting and reshaping data, pivoting, sorting, and preparing datasets for analysis. You will also use Matplotlib to create meaningful visualizations such as line charts, scatter plots, histograms, bar charts, and heatmaps.

The second part of the course introduces the foundations of Artificial Intelligence and Machine Learning, including AI concepts, history and applications, Natural Language Processing, ethical and societal implications, and the relationship between AI and other technologies. You will explore important Python libraries used in AI/ML, including Scikit-Learn, TensorFlow, Keras, PyTorch, NLTK, XGBoost, CatBoost, and OpenCV.You will then explore supervised and

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