The concept of Artificial Intelligence and Machine Learning can be a little bit intimidating for beginners, and specifically for people without a substantial background in complex math and programming. This training is a soft starting point to walk you through the fundamental theoretical concepts. In this course, you’re going to open the mysterious AI/ML black-box, and take a look inside, get more familiar with the terms being used in the industry. It is going to a super interesting story. It is important to mention that there are no specific prerequisites for starting this training, and it is designed for absolute beginners.
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- Access 28 lectures & 2 hours of content 24/7
- Understand the difference between Applied & Generalized AI
- Learn the process of training a model
- Learn more about Machine Learning & Deep Learning
- Understand clustering & dimension reduction
The Machine Learning for Absolute Beginners training program is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. The training is divided into multiple levels, and each level is covering a group of related topics for continuous step by step learning. The second course, as part of the training program, aims to help you start your practical journey. You will learn the Python fundamentals and the amazing Pandas data science library. Each section has a summary exercise as well as a complete solution to practice new knowledge.
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- Access 41 lectures & 3 hours of content 24/7
- Develop data science projects using Python syntax
- Use JupyterLab tool for Jupiter notebooks
- Load large datasets from files using Pandas
- Perform data analysis & exploration
- Perform data cleaning & transformation as a pre-processing step before moving into machine learning algorithms
This third course as part of the training program aims to help you to perform Exploratory Data Analysis (EDA) by visualizing a dataset using a variety of charts. You will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries, including Matplotlib and Seaborn fundamentals, charts, and more. Each section has a summary exercise as well as a complete solution to practice new knowledge.
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- Access 39 lectures & 2 hours of content 24/7
- Perform Exploratory Data Analysis (EDA) for any dataset
- Visualize data using a variety of chart types
- Learn Matplotlib & Seaborn fundamentals
- Create bar, grouped bar, stacked bar & lollipop charts
- Create pie, tree-map charts
- Create line, area, stacked area charts
- Create histogram, density, box-and-whisker & swarm charts
- Create scatter, correlogram, heat-map, hexbin-map charts
via Ashraf
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