What you’ll learn
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The course provides the entire toolbox you need to become a data scientist
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Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
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Impress interviewers by showing an understanding of the data science field
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Learn how to pre-process data
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Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
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Start coding in Python and learn how to use it for statistical analysis
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Perform linear and logistic regressions in Python
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Carry out cluster and factor analysis
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Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
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Apply your skills to real-life business cases
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Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
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Unfold the power of deep neural networks
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Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
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Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
Who this course is for:
- You should take this course if you want to become a Data Scientist or if you want to learn about the field
- This course is for you if you want a great career
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
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