Right now, despite the Covid-19 economic contraction, traditional businesses are hiring data scientists in droves! Therefore, data scientist has become the top job in the U.S. for the last four years running.

However, data science has a difficult learning curve. This course seeks to fill all those gaps and has a comprehensive syllabus that tackles all the major components of data science knowledge.

You will be using data science to solve common business problems throughout this course. You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. Then, you will learn visualization theory for data science and analytics using Seaborn, Matplotlib, and Plotly.

You will look at dashboard design using Google Data Studio along with machine learning and deep learning theory/tools.

Then, you will be solving problems using predictive modeling, classification, and deep learning. After this, you will move your focus to data analysis and statistical case studies, data science in marketing, and data science in retail.

Finally, you will see deployment to the cloud using Heroku to build a machine learning API.

By the end of this course, you will learn all the major components of data science and gain the confidence to enter the world of data science.

All the code files and the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Data-Science-Analytics-AI-for-Business-the-Real-World-

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Spis treści

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