Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 41 Minute(s)
Language
English
Taught by
Packt Publishing
Rating
Course Overview
Fast-track your data analysis journey with Python using its powerful libraries
Python is undoubtedly one of the most popular programming languages that’s being extensively used in the field of data science. There is a rapid increase in the number of data and so for the demand of experts who can analyze these big chunk of data. So if you have basic Python knowledge and want to explore powerful data analysis techniques, then go for this Learning Path.
Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. The highlights of this Learning Path are:
- Get solutions to your common and not-so-common data science problems
- Highly practical, real world examples that make data science your comfort zone
- Understand why is Mastering python data analysis with Pandas really useful
Let’s take a look at your learning journey. You will be introduced to the field of data science using Python tools to manage and analyze data. You will learn some of the fundamental tools of the trade and apply them to real data problems. Along the way, the Learning Path discusses the use of Python stack for data analysis and scientific computing, and expands on concepts of data acquisition, data cleaning, data analysis, and machine learning. You will learn how to apply Pandas to important but simple financial tasks such as modeling portfolios, calculating optimal portfolios based upon risk, and much more.
On completion of this Learning Path, you will become an expert in analyzing your data efficiently using Python.
Meet Your Expert:
We have the best works of the following esteemed authors to ensure that your learning journey is smooth:
- Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a Ph.D. in information retrieval from the Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems.
- Prabhat Ranjan has extensive industry experience in Python, R, and machine learning. He has a passion for using Python, Pandas, and R for various new, real-time project scenarios. He is a passionate and experienced trainer when it comes to teaching concepts and advanced scenarios in Python, R, data science, and big data Hadoop. His teaching experience and strong industry expertise make him the best in this arena.
Course Content
- 2 section(s)
- 33 lecture(s)
- Section 1 Data Analysis with Python
- Section 2 Mastering Python Data Analysis with Pandas
What You’ll Learn
- Installation of the core Python tools required for data analysis, Explore the different data types in Python, UseNumPy for fast array computation, Use Pandas for data analysis, Frame a data science problem and use Python tools to solve it, Read and write data in text format, Master concepts involved in interacting with databases
Skills covered in this course
Reviews
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RRichard Irwin
I think this course is quite in-depth, however, the format for teaching was not to my particular style. I would have preferred if we typed as we were learning, not just given all the code to run as the lectures were happening. That aside, I did type out all the notes then started the lectures and found I could add more detailed notes. I'm not sure if someone went through the code on a fresh install of conda/Python as one of the commands did not work, which popped up quite frequently in the second set of lectures whilst learning about chinook, there were no instructions of how to find the correct database or even SQLiteStudio. You will need to sort out the Quizzes as well, considering it shows you the right answer in brackets. That said, this course did make me research into problems I came into and to get a further definition into varies functions, so for that I would say it made me think a lot more and would be akin to real-life situations. I think with a few minor tweaks this course could be improved. I stand by the 4 star considering the in-depth knowledge that is contained in this course, which gives you a wider range of subjects to explore after this course.
