Python is one of the most widely-used programming languages among data scientists. This course will show you the technical advantages it has over other programming languages. You will start working with its modules for scientific computing, and you will begin to understand why these functionalities make Python the preferred choice in finance, econometrics, economics, data science, and machine learning.
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In this section, we will introduce you to the concept of programming and will talk about some of Python’s key features (it is an open-source, general-purpose, high-level language). We will show you how to install the Jupyter Notebook (the environment we will use to code in Python) and will introduce you to its interface and dashboard.
This is where you will start coding and learn one of the most fundamental concepts in programming – working with variables.
If you want to master Python programming, there is no way around learning basic Python syntax operators first. In this section, we will cover the double equality sign, reassigning of values, adding comments, line continuation, indexing elements, arithmetic operators, comparison operators, logical operators, and identity operators.
In this section, we will explore more operators used in Python. More precisely, we will first learn about the comparison operators, which will obviously allow you to compare different values in your code. Then, we will focus on the logical operators AND, OR, and NOT. We will conclude by a few examples with the identity operators IS and IS NOT.
Conditional statements are the bread and butter of programming. Here, you will start creating your own IF, ELSE, and ELIF statements.
Python functions are another invaluable tool for programmers. They allow you to carry out pre-defined or specifically-designed operations that manipulate the data you are working with and bring it one step closer to representing a meaningful output.
Sequences are one of the main building blocks of computer programming. A sequence helps you store and organize different values you are working with. We will teach you how to work with lists, list slicing, tuples, and dictionaries.
Iterations are a programming technique which allows you to execute certain code repeatedly. This is one of the instruments letting you to automate repeated tasks and benefit from one of its main strong points.
This course is part of Module 2 of the 365 Data Science Program. The complete training consists of four modules, each building upon your knowledge from the previous one. In contrast to the introductory nature of Module 1, Module 2 is designed to tackle all aspects of programming for data science. You will learn how to work with relational databases and SQL, as well as how to code in Python and R. By the end of this Module, you will have a versatile programming skill set.See All Modules
Real-life project and data. Solve them on your own computer as you would in the office.
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The course is in-depth and is delivered at a steady pace with eye catching visuals. The instructors go through all the basics really well. They try not to over-simplify the material, you get a good sense аof how deep Data Science is in the course. Great job!!!
This course is amazing! After watching the video carefully and doing all the exercises, I am even capable of having discussions with Machine learning major Master’s students! High standard course with reasonable pricing.
Very clear and in-depth explanation of data science and how all the inter-related concepts apply in real life business environment. Absolutely great for beginners! Best data science course I have come across so far!
I would highly recommend the course to any beginner who wants to venture into the world of Data Science. The concepts are very well explained and there is an emphasis on practical application which really helps create a better understanding of the concepts.