Python real world data science

! R 20 16 EW N FO Python Real-World Data Science CURATED COURSE Python Real-World Data Science A course in four modules Unleash the power of Python and its robust data science capabilities with your Course Guide Ankita Thakur Learn to use powerful Python libraries for effective data processing and analysis To contact your Course Guide Email: ankitat@packtpub.com BIRMINGHAM - MUMBAI Meet Your Course Guide Hello and welcome to this Data Science with Python course You now have a clear pathway from learning Python core features right through to getting acquainted with the concepts and techniques of the data science field—all using Python! This course has been planned and created for you by me Ankita Thakur – I am your Course Guide, and I am here to help you have a great journey along the pathways of learning that I have planned for you I've developed and created this course for you and you'll be seeing me through the whole journey, offering you my thoughts and ideas behind what you're going to learn next and why I recommend each step I'll provide tests and quizzes to help you reflect on your learning, and code challenges that will be pitched just right for you through the course If you have any questions along the way, you can reach out to me over e-mail or telephone and I'll make sure you get everything from the course that we've planned – for you to start your career in the field of data science Details of how to contact me are included on the first page of this course What's so cool about Data Science? What is Data Science and why is there so much of buzz about this in the world? Is it of great importance? Well, the following sentence will answer all such questions: "This hot new field promises to revolutionize industries from business to government, health care to academia." – The New York Times The world is generating data at an increasing pace Consumers, sensors, or scientific experiments emit data points every day In finance, business, administration, and the natural or social sciences, working with data can make up a significant part of the job Being able to efficiently work with small or large datasets has become a valuable skill Also, we live in a world of connected things where tons of data is generated and it is humanly impossible to analyze all the incoming data and make decisions Human decisions are increasingly replaced by decisions made by computers Thanks to the field of Data Science! Data science has penetrated deeply in our connected world and there is a growing demand in the market for people who not only understand data science algorithms thoroughly, but are also capable of programming these algorithms A field that is at the intersection of many fields, including data mining, machine learning, and statistics, to name a few This puts an immense burden on all levels of data scientists; from the one who is aspiring to become a data scientist and those who are currently practitioners in this field Treating these algorithms as a black box and using them in decision-making systems will lead to counterproductive results With tons of algorithms and innumerable problems out there, it requires a good grasp of the underlying algorithms in order to choose the best one for any given problem Python as a programming language has evolved over the years and today, it is the number one choice for a data scientist Python has become the most popular programming language for data science because it allows us to forget about the tedious parts of programming and offers us an environment where we can quickly jot down our ideas and put concepts directly into action It has been used in industry for a long time, but it has been popular among researchers as well In contrast to more specialized applications and environments, Python is not only about data analysis The list of industrial-strength libraries for many general computing tasks is long, which makes working with data in Python even more compelling Whether your data lives inside SQL or NoSQL databases or is out there on the Web and must be crawled or scraped first, the Python community has already developed packages for many of those tasks Course Structure Frankly speaking, it's a wise decision to know the nitty-gritty of Python as it's a trending language I'm sure you'll gain lot of knowledge through this course and be able to implement all those in practice However, I want to highlight that the road ahead may be bumpy on occasions, and some topics may be more challenging than others, but I hope that you will embrace this opportunity and focus on the reward Remember that we are on this journey together, and throughout this course, we will add many powerful techniques to your arsenal that will help us solve even the toughest problems the data-driven way I've created this learning path for you that consist of four models Each of these modules are a mini-course in their own way, and as you complete each one, you'll have gained key skills and be ready for the material in the next module So let's now look at the pathway these modules create—basically all the topics that will be exploring in this learning journey Course Journey We start the course with our very first module, Python Fundamentals, to help you get familiar with Python Installing Python correctly is equal to half job done This module starts with the installation of Python, IPython, and all the necessary packages Then, we'll see the fundamentals of object-oriented programming because Python itself is an object-oriented programming language Finally, we'll make friends with some of the core concepts of Python—how to get Python programming basics nailed down Then we'll move towards the analysis part The second module, Data Analysis, will get you started with Python data analysis in a practical and example-driven way You'll see how we can use Python libraries for effective data processing and analysis So, if you want to to get started with basic data processing tasks or time series, then you can find lot of hands-on knowledge in the examples of this module The third module, Data Mining, is designed in a way that you have a good understanding of the basics, some best practices to jump into solving problems with data mining, and some pointers on the next steps you can take Now, you can harness the power of Python to analyze data and create insightful predictive models Finally, we'll move towards exploring more advanced topics Sometimes an analysis task is too complex to program by hand Machine learning is a modern technique that enables computers to discover patterns and draw conclusions for themselves The aim of our fourth module, Machine Learning, is to provide you with a module where 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 So, if you want to become a machine-learning practitioner, a better problem solver, or maybe even consider a career in machine learning research, I'm sure there is lot for you in this module! The Course Roadmap and Timeline Here's a view of the entire course plan before we begin This grid gives you a topic overview of the whole course and its modules, so you can see how we will move through particular phases of learning to use Python, what skills you'll be learning along the way, and what you can with those skills at each point I also offer you an estimate of the time you might want to take for each module, although a lot depends on your learning style how much you're able to give the course each week! Table of Contents Course Module 1: Python Fundamentals Chapter 1: Introduction and First Steps – Take a Deep Breath A proper introduction Enter the Python About Python Portability 9 Coherence 9 Developer productivity An extensive library 10 Software quality 10 Software integration 10 Satisfaction and enjoyment 10 What are the drawbacks? 11 Who is using Python today? 11 Setting up the environment 11 Python versus Python – the great debate 12 What you need for this course 13 Installing Python 14 Installing IPython 14 Installing additional packages 16 How you can run a Python program 17 Running Python scripts 18 Running the Python interactive shell 18 Running Python as a service 20 Running Python as a GUI application 20 How is Python code organized 21 How we use modules and packages 22 [i] .. .Python Real-World Data Science A course in four modules Unleash the power of Python and its robust data science capabilities with your Course Guide Ankita Thakur Learn to use powerful Python. .. your career in the field of data science Details of how to contact me are included on the first page of this course What's so cool about Data Science? What is Data Science and why is there so... Thanks to the field of Data Science! Data science has penetrated deeply in our connected world and there is a growing demand in the market for people who not only understand data science algorithms