Data Analyst career track course Basically is the part of Data science and it's data science best course.
A Data analyst is the key role that plays for a company to take great and profitable decisions made by the data analysis.
The data analyst is a dream job that most of the data science practitioners want. in 2021 and coming years there will be thousands of new job openings for the post of data analyst.
The career track of data analyst course is made up of 10 courses those are the back bones to establish you as a data analyst.
In this post we will discuss each of them in detail.
The 10 Parts of data analyst course are as follows.
Working with data is an essential part of maintaining a healthy business. This course will introduce you to the field of data science, help you understand the various processes and distinguish between terms such as: ‘traditional data,’ ‘big data,’ ‘business intelligence,’ ‘business analytics,’ ‘data analytics,’ ‘data science,’ and ‘machine learning.’
What You'll Learn
You are interested in starting a career in data science? Begin with the very basics by receiving the proper introduction to the world of data with this course!
Distinguish between various data science related fields
Understand the terms traditional and big data
Integrate common data science techniques
Use specific data science tools
What are the most common data science programming languages
Become familiar with the data science job positions and alternatives
Even in data science, smaller datasets are processed quicker in Excel rather than Python, R, or SQL. This course gives you the skills you need to crunch numbers in the spreadsheet software program.
83 Lessons
4 Hours
Course Overview
Microsoft Excel is the #1 productivity software in the world. A huge amount of data comes in a spreadsheet format, so an analyst needs Excel in their arsenal. This course will teach you all the Excel skills you need to perform multi-layered calculations, create charts, manipulate data, look up functions, and more!
What You'll Learn
Every data analyst needs Excel in their arsenal. This course will teach you how to apply various Excel techniques for performing calculations, data manipulations, analyses, and more!
Covering descriptive and inferential statistics, as well as hypothesis testing techniques and exercises, statistics puts the “scientist” in data scientist.
43 Lessons
3 Hours
Course Overview
Statistics is the driving force in any quantitative career. It is the fundamental skill that a data scientist needs in order to understand and design statistical tests and analysis using modern software packages and programming languages. In this course, we start from the very basics and gradually build your statistical thinking. This, in turn, enables you to understand the more complex analyses carried out later in the program.
What You'll Learn
This course begins with the very basics of statistics and builds up your arithmetic thinking. It gradually teaches you how to work with more complex analyses, statistical approaches, and hypothesis.
Distinguish between the diverse types of data and levels of measurement
Equipping you with the essential data science skills to effectively manage relational databases by extracting, transforming, and loading your data.
114 Lessons
8 Hours
Course Overview
SQL is one of the fundamental programming languages you need to learn to work with databases. When you are a data scientist in a company and you need data to perform your analysis, you usually have two options: extract it on your own or contact the IT team. Of course, the ability to extract your own data is an extremely valuable skill to have. In this course, we will teach you everything you need to know in terms of database management and creating SQL queries.
What You'll Learn
SQL is a must if you are expected to work with databases. This course is the ultimate guide, teaching you everything you need to know in terms of database management and creating SQL queries.
Understand relational database management systems
Study the components of SQL
Store, retrieve, and manipulate data from relational databases
Know how to set up a connection between Workbench and the server
Laying the foundations of programming in Python to prepare you for deploying machine and deep learning algorithms later in the training.
40 Lessons
2 Hours
Course Overview
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.
What You'll Learn
This course will introduce you to the Python world. You will learn about Python technical advantages, specific features, modules, functionalities, and more.
Basic Python syntax
Work with variables, operators, and conditional statements
Teaching you how to master the art of creating and styling charts to achieve professional results. The course is based in four different technologies – Excel, Tableau, Python, and R – to complete your data visualization skillset.
100 Lessons
9 Hours
Course Overview
The Data Visualization course is designed for everyone looking to deepen their understanding of creating meaningful and compelling visualizations.
Whether you’re coming from a business or data science-related field, knowledge in data visualization is both important and advantageous.
That’s precisely why this course is centered not in just one, but four different environments: Excel, Tableau, Python, and R. Each section is dedicated to a specific type of chart – bar charts, pie charts, area charts, line charts and many more.
In addition, there are lectures that specifically explore what to avoid when creating a certain graphic.
You can stick with your preferred environment and follow each section. Or you could master all four environments and add indispensable skills to your data visualization tool set.
What You'll Learn
This course features four technologies through which you can learn data visualization – Excel, Tableau, Python and R. Even if you’re a complete beginner, this course will build your data viz skillset, starting with basics like the bar chart, and building up towards combination charts and dashboards.
This course will guide you through one of Python’s most notable packages – NumPy. We’ll explain why it’s so popular and discuss the numerous applications of its crown jewel – the ndarray class.
67 Lessons
7 Hours
Course Overview
This course is designed to show you how to work with one of Python’s fundamental packages – NumPy. You will learn what a “package” is and see how to install, upgrade and import it.
By the time you finish the course, you’ll be comfortable with NumPy’ ndarray class, how to slice and reduce the dimensions of its instances, as well as how to quickly refer to the documentation.
Furthermore, you’ll be ready to take advantage of NumPy’s various built-in functions and methods, which we’ll use to generate random and non-random data, import and export data to and from Python, find statistical values for a dataset, and clean and preprocess ndarrays.
What You'll Learn
Do you already know how to use Python? Improve your skills by adding another tool to your arsenal – one of the most notable packages, NumPy!
Create arrays with NumPy
Use basic NumPy syntax
Generate data with NumPy
Implement statistical functions
Substitute missing values in Ndarrays
Explore ways to clean and preprocess data in NumPy
Introducing you to the fundamentals of the quintessential Python data analysis library, pandas, and its core data structures – the Series and DataFrame objects.
27 Lessons
2 Hours
Course Overview
pandas is one of today’s most successful data analysis libraries out there. A favorite to many, its versatile functionalities can be leveraged for manipulation of many types of data - numeric, text, Boolean, and more.
That’s one of the features that make pandas the go-to choice for analysts, especially during the data cleaning and preprocessing stages.
Technically, pandas has been built on NumPy because the former needs the computational power and abilities of the latter.
But what makes pandas truly great is its ability to operate with the data in an easy-to-use way, allowing you to focus almost entirely on your analytic task.
And in this course, you will learn how to work with this powerful Python library and its core data structures – the pandas Series and DataFrames.
What You'll Learn
This course delivers information about one of the most widely used data analysis libraries – pandas. Learn pandas and solve your analytic tasks in an easy and professional way!
Develop a basic understanding of the pandas library
Navigate through the pandas documentation
Practice with fundamental programming tools
Study collecting, cleaning, and preprocessing data
A hands-on course covering SQL setup and fundamental components, combined with a guided walkthrough of 10 mock interviews with real-world SQL interview questions and expert tips on how to pass them successfully.
23 Lessons
2 Hours
Course Overview
This practical course helps you ace the SQL part of any data science job interview and get hired.
The 5-step framework and 10 mock interviews will prepare you to tackle any SQL interview question with ease.
You will find out what interviewers want to hear from you, how to master your interaction with them, and how to answer even the challenging follow-up questions.
By the end of the course, you will have done this at least 10 times. So, when the real interview comes, it will feel like just another practice round.
What You'll Learn
This course will help you build a deliberate strategy when participating in a data scientist job interview involving SQL. It will provide you with confidence and methodology for demonstrating the required skills appropriately.
Build a winning strategy for data science interviews
How to stay focused during mock interviews
Improve your communication skills and interview style
Providing you with the skillset required for manipulating date and time values in Python. Includes a practical example where you will work with a sales company’s dataset to put your theoretical knowledge into action.
22 Lessons
2 Hours
Course Overview
Dates and Times in Python is the course that will take your data analyst skillset to the next level!
The ability to adjust dates and time according to a specific territory is crucial across numerous businesses and industries.
In this course, you will master handling both date values that depend on the structure of the different calendars used across the globe, and time values that reflect time-saving regulations, clock changes, and time conversions.
You will also discover how to keep track of historical data, use specific date- and time-related libraries, classes, methods, and conversion techniques in Python.
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