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Data Analytics Bootcamp: Project 1 Data Visualization: A Practical Introduction for Absolute Beginners Self-Paced Learning
Self-Paced
Learning Style
Course
Learning Style
Beginner
Difficulty
14 Days
Course Duration
Course Info
Certificate
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9:00 AM - 5:00 PM CST
Duration - 0 Days -
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With latest trends of digital worlds and social networking, a tremendous amount of data is being generated every minute. Data hides great treasure that can be mined, understood and then extra useful value for the industry in the real world.
This project will test your approach towards the importance of data and analytical skills through data analysis tasks.
Course Information
With latest trends of digital worlds and social networking, a tremendous amount of data is being generated every minute. Data hides great treasure that can be mined, understood and then extra useful value for the industry in the real world.
This project will test your approach towards the importance of data and analytical skills through data analysis tasks.
Outline
More Information
| Subjects | Big Data |
|---|---|
| Lab Access | No |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Beginner |
| Course Duration | 14 Days |
| Language | English |
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Course Expert:
Tom Robertson
(Data Science Enthusiast)
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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