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The Data Science Course 2020: Complete Data Science Bootcamp

The Data Science Course 2020: Complete Data Science Bootcamp

The Data Science Course 2019: Complete Data Science Bootcamp
The Data Science Course 2020: Complete Data Science Bootcamp, Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning
BESTSELLER
Created by 365 Careers, 365 Careers Team
English
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What you'll learn
  • The course provides the entire toolbox you need to become a data scientist
  • 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
  • Impress interviewers by showing an understanding of the data science field
  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
  • Requirements
  • No prior experience is required. We will start from the very basics
  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Microsoft Excel 2003, 2010, 2013, 2016, or 365
  • Description

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