Applied Data Analysis: Working in Organizations and Industries
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About this course
This course is a master class in data analysis and is a continuation of the Microsoft Professional Program in Data Analysis.
Even though the basis of data analysis follows a pattern common to all, despite its application in a multitude of various industries and organizations , there are however some changes and considerations one has to keep in mind when it comes to different industries. Being proficient at these specifications of analyzing data with respect to different industries and organizations is a unique skill set and one that is highly sought after by employers. This course aims to help students gain a hands on approach and learn how data analysis works in the context of different industries so as to give them a practical idea of working with a variety of organizations which require data analysis.
This course is targeted at those data analysts who wish to gain a higher skill set and be proficient at their work.
Upon completion of this course, the participant should have an advanced skill set and a sound working knowledge of the following principals while also be able to;
- Gain a basic understanding of data analysis in the context of various industries and their specific requirements.
- Gain a hands on practical experience with fundamental data analysis techniques and the specific ones which may be needed when it comes to adapting to different circumstances.
- Learn how to efficiently work with different kinds of data.
- Practice and try different roles in data analysis to see which is a better fit for the participant
- Explore new opportunities in the world of data analysis and how to further enrich and expand their careers.
This particular course is aimed at the following audience;
- data analysts
The following prerequisites are absolutely necessary to be eligible to take this" Applied Data Analysis: Working in Organizations and Industries course";
- Proficiency at the basic use of Microsoft Excel
- A fundamental background in math and statistics
- Data visualization fluency
|Learning Style||Self-Paced Learning|
|Course Duration||24 Hours|
(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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