Hey everyone, this post is a part of my IBM Professional Data Engineer Certificate by Coursera learning experience. The certificate program is a 13 part series. This post is related to the second course in the series. The course covers some basic concepts of Python and some additional topics that are generally used in Data Engineering projects. Please keep in mind that the course is introductory course, you will have to deep dive to become more proficient in the subject.
Why take this course?
This course is a part of the program, upon completing the course, you will be receiving a shareable certificate that you can share on social media platforms such as LinkedIn and on your personal website.
If you are not someone that is looking to complete the program but wanted to learn Python basics, I highly recommend auditing the course. In that way, you don’t have to pay for the course and you can get the content you wanted to learn except that you cannot complete quizzes.
Let us have a quick overview of what the course has to offer.
Week 1
As mentioned earlier, this course cover basics of Python. In first week content, you will have get introduced to data types, expressions, variables and basic String operations.
Week 2
In this week, you will learn about collection data types in Python i.e., Lists, Tuples, Dictionaries and Sets. You will get a chance to learn about limitations of each data type and their use cases and also some basic operations that are used in day to day projects.
Week 3
The course introduces you to Conditions, Loops, Functions (basic built-in functions and user-defined functions), Exception Handling, Objects and Classes.
Week 4
This is where it gets interesting, you will be using most of the concepts that you have learned in previous weeks by learning Files, Pandas and NumPy. To those who are new to python, Pandas and NumPy are python libraries that are very commonly used in Data Engineering projects.
With Pandas tutorial, you will get introduced to DataFrames and some basic df operations. You will get to work with data, such as reading csv files or excel files, working on the dataframe and saving the results to a csv file or excel file.
In NumPy tutorial, you will get introduced to NumPy arrays and some attributes such as type, size, shape, ndim. You will also learn about multi-dimensional arrays.
Week 5
Being a data engineer, you will have a chance to interact with a lot of websites and data that website has to offer. This week, you will get a chance to learn about APIs which are the building blocks of exchanging data and other information.
You will have a chance to learn about build block of APIs, REST APIs and HTTP Requests. You will see what are the different HTTP Methods, URL.
A brief introduction to Web scraping through HTML tags and Python programming.
Overall, I have come to learn a lot from different tools to areas of improvement in my skillset. The course offers labs that will help you to implement the skills you are learning as you go which is a good thing. End of the day, it is up to you to enhance your skills and keep learning.
