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Complete Data Analyst Training: Python, NumPy, Pandas, Data Collection, Preprocessing, Data Types, Data Visualization
An excellent training about Business Analytics & Intelligence
The Data Analyst Course: Complete Data Analyst Bootcamp 2021
The problemMost data analyst, data science, and coding courses miss a critical practical step. They dont teach you how to work with raw data, how to clean, and preprocess it. This creates a sizeable gap between the skills you need on the job and the abilities you have acquired in training. Truth be told, real-world data is messy, so you need to know how to overcome this obstacle to become an independent data professional. The bootcamps we have seen online and even live classes neglect this aspect and show you how to work with clean data. But this isnt doing you a favour. In reality, it will set you back both when you are applying for jobs, and when youre on the job. The solutionOur goal is to provide you with complete preparation. And this course will turn you into a job-ready data analyst. To take you there, we will cover the following fundamental topics extensively. Theory about the field of data analyticsBasic PythonAdvanced PythonNumPyPandasWorking with text filesData collectionData cleaningData preprocessingData visualizationFinal practical exampleEach of these subjects builds on the previous ones. And this is precisely what makes our curriculum so valuable. Everything is shown in the right order and we guarantee that you are not going to get lost along the way, as we have provided all necessary steps in video (not a single one skipped). In other words, we are not going to teach you how to analyse data before you know how to gather and clean it. So, to prepare you for the entry-level job that leads to a data science position – data analyst – we created The Data Analyst Course. This is a rather unique training program because it teaches the fundamentals you need on the job. A frequently neglected aspect of vital importance. Moreover, our focus is to teach topics that flow smoothly and complement each other. The course provides complete preparation for someone who wants to become a data analyst at a fraction of the cost of traditional programs (not to mention the amount of time you will save). We believe that this resource will significantly boost your chances of landing a job, as it will prepare you for practical tasks and concepts that are frequently included in interviews. The topics we will cover1. Theory about the field of data analytics2. Basic Python3. Advanced Python4. NumPy5. Pandas6. Working with text files7. Data collection8. Data cleaning9. Data preprocessing10. Data visualization11. Final practical example1. Theory about the field of data analyticsHere we will focus on the big picture. But dont imagine long boring pages with terms youll have to check up in a dictionary every minute. Instead, this is where we want to define who a data analyst is, what they do, and how they create value for an organization. Why learn it?You need a general understanding to appreciate how every part of the course fits in with the rest of the content. As they say, if you know where you are going, chances are that you will eventually get there. And since data analyst and other data jobs are relatively new and constantly evolving, we want to provide you with a good grasp of the data analyst role specifically. Then, in the following chapters, we will teach you the actual tools you need to become a data analyst.2. Basic PythonThis course is centred around Python. So, well start from the very basics. Dont be afraid if you do not have prior programming experience. Why learn it?You need to learn a programming language to take full advantage of the data-rich world we live in. Unless you are equipped with such a skill, you will always be dependent on other peoples ability to extract and manipulate data, and you want to be independent while doing analysis, right? Also, you dont necessarily need to learn many programming languages at once. It is enough to be very skilled at just one, and weve naturally chosen Python which has established itself as the number one language for data analysis and data science (thanks to its rich libraries and versatility).3. Advanced PythonWe will introduce advanced Python topics such as working with text data and using tools such as list comprehensions and anonymous functions. Why learn it?These lessons will turn you into a proficient Python user who is independent on the job. You will be able to use Pythons core strengths to your advantage. So, here it is not just about the topics, it is also about the depth in which we explore the most relevant Python tools.4. NumPyNumPy is Pythons fundamental package for scientific computing. It has established itself as the go-to tool when you need to compute mathematical and statical operations. Why learn it?A large portion of a data analysts work is dedicated to preprocessing datasets. Unquestionably, this involves tons of mathematical and statistical techniques that NumPy is renowned for. In addition, the package introduces multi-dimensional array structures and provides a plethora of built-in functions and methods to use while working with them. In other words, NumPy can be described as a computationally stable state-of-th
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