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Python for Machine Learning and Artificial Intelligence, Essentials
This course introduces students to the Python programming language essential for data manipulation, statistical analysis, and modeling techniques required for machine learning and artificial intelligence.
We will explore the wonderfully concise and expressive use of Python’s advanced module features and apply it in probability, statistical testing, signal processing, and various other applications.
Students will explore mathematical operations with array data structures, optimization, probability density function, interpolation, fast Fourier transform, basic signal processing, and other high-performance benefits of core scientific packages such as NumPy, SciPy, sklearn and scikit-learn, and Matplotlib.
Once you gain a deep understanding of the practical aspects of Python for data wrangling involved in ML and AI applications, you will be a more effective problem solver when dealing with engineering and scientific challenges in your own career.
At the conclusion of the course, the student should be able to:
- Solve complex engineering, financial, mathematical, and scientific problems.
- Develop complex functions and scripts to perform complicated calculations and to visualize the results of these calculations.
- Attain deeper understanding of the mathematical toolkit provided by powerful core packages.
- Acquire in-depth, hands-on experience.
- Install and configure Python and essential Python development tools.
- Write Python programs, and run them to generate tabular and graphical results.
- Manage and manipulate data, perform data type conversions, merge datasets, deal with missing values, and extract, delete, or transform subsets of data based on logical criteria.
- Use Python to perform basic data analysis using data exploration, statistical analysis, and machine learning and AI techniques.
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