Duration : 43.5 hours
What you’ll learn
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Become a Data Scientist and get hired
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Master Machine Learning and use it on the job
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Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
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Use modern tools that big tech companies like Google, Apple, Amazon and Facebook use
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Present Data Science projects to management and stakeholders
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Learn which Machine Learning model to choose for each type of problem
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Real life case studies and projects to understand how things are done in the real world
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Learn best practices when it comes to Data Science Workflow
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Implement Machine Learning algorithms
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Learn how to program in Python using the latest Python 3
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How to improve your Machine Learning Models
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Learn to pre process data, clean data, and analyze large data.
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Build a portfolio of work to have on your resume
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Developer Environment setup for Data Science and Machine Learning
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Supervised and Unsupervised Learning
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Machine Learning on Time Series data
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Explore large datasets using data visualization tools like Matplotlib and Seaborn
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Explore large datasets and wrangle data using Pandas
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Learn NumPy and how it is used in Machine Learning
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A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
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Learn to use the popular library Scikit-learn in your projects
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Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
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Learn to perform Classification and Regression modelling
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Learn how to apply Transfer Learning
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