The “Akamai Network Engineering Professional Certificate” is a specialized program dedicated to developing expertise in network engineering with a focus on content delivery and cloud services. This certificate covers key concepts in designing, optimizing, and managing networks for improved performance and security. Learn about content distribution, traffic management, and cloud technologies. By completing this certificate, you’ll be well-equipped to excel as a network engineer in the dynamic landscape of content delivery and online services.

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About The Course

Data Analysis has been around for a long time. But up until a few years ago, developers practiced it using expensive, closed-source tools like Tableau. But recently, Python, SQL, and other open libraries have changed Data Analysis forever. In the Data Analysis with Python Certification, you’ll learn the fundamentals of data analysis with Python. By the end of this certification, you’ll know how to read data from sources like CSVs and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.

What Will You Learn

You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn.
You will learn how to use the pandas library, one of the most powerful tools for data manipulation in Python.
This knowledge helps you assess the effectiveness of models and select the best ones for deployment.

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Course Contents

Introduction to Data Analysis

Data analysis is the act of turning raw, messy data into useful insights by cleaning the data up, transforming it, manipulating it, and inspecting it.

Data Manipulation with pandas

Introduction to pandas library and its data structures (DataFrame, Series) Data cleaning and preprocessing techniques Data transformation, filtering, and aggregation Handling missing data and outliers

Statistical Analysis with NumPy and SciPy

Introduction to NumPy and its array-based computing capabilities Statistical functions for data analysis (mean, median, variance, etc.) Hypothesis testing and statistical significance

FAQ

What skills do I need to have before enrolling in the course?

While prior knowledge of data analytics is not always required, having basic mathematical skills and familiarity with computer applications can be beneficial. Some courses are designed for beginners and assume no prior experience.

Are there any real-world projects or case studies?

Yes, most data analytics courses include real-world projects and case studies where you can apply your learned skills to practical scenarios using real datasets.

Will the course cover data ethics and privacy considerations?

Yes, responsible data handling and ethical considerations are often covered, highlighting the importance of data privacy and security.