About This Book
- Unleash the power of Python 3 objects
- Learn to use powerful Python libraries for effective data processing and analysis
- Harness the power of Python to analyze data and create insightful predictive models
- Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics
Who This Book Is For
Entry-level analysts who want to enter in the data science world will
find this course very useful to get themselves acquainted with Python’s
data science capabilities for doing real-world data analysis.
What You Will Learn
- Install and setup Python
- Implement objects in Python by creating classes and defining methods
- Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis
- Create effective visualizations for presenting your data using Matplotlib
- Process and analyze data using the time series capabilities of pandas
- Interact with different kind of database systems, such as file, disk format, Mongo, and Redis
- Apply data mining concepts to real-world problems
- Compute on big data, including real-time data from the Internet
- Explore how to use different machine learning models to ask different questions of your data
In Detail
The Python: Real-World Data Science course will take you on
a journey to become an efficient data science practitioner by
thoroughly understanding the key concepts of Python. This learning path
is divided into four modules and each module are a mini course in their
own right, and as you complete each one, you’ll have gained key skills
and be ready for the material in the next module.
The course begins with getting your Python fundamentals nailed down.
After getting familiar with Python core concepts, it’s time that you
dive into the field of data science. In the second module, you'll learn
how to perform data analysis using Python in a practical and
example-driven way. The third module will teach you how to design and
develop data mining applications using a variety of datasets, starting
with basic classification and affinity analysis to more complex data
types including text, images, and graphs. Machine learning and
predictive analytics have become the most important approaches to
uncover data gold mines. In the final module, we'll discuss the
necessary details regarding machine learning concepts, offering
intuitive yet informative explanations on how machine learning
algorithms work, how to use them, and most importantly, how to avoid the
common pitfalls.
