Become a Python Data Analyst

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    Course

  • Methodology

    Online

  • Start date

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Take your data analytics and predictive modeling skills to the next level using the popular tools and libraries in Python.The Python programming language has become a major player in the world of Data Science and Analytics. This course introduces Python’s most important tools and libraries for doing Data Science; they are known in the community as “Python’s Data Science Stack”.This is a practical course where the viewer will learn through real-world examples how to use the most popular tools for doing Data Science and Analytics with Python.About The Author
.
Alvaro Fuentes is a Data Scientist with an M.S. in Quantitative Economics and a M.S. in Applied Mathematics with more than 10 years of experience in analytical roles. He worked in the Central Bank of Guatemala as an Economic Analyst, building models for economic and financial data. He founded Quant Company to provide consulting and training services in Data Science topics and has been a consultant for many projects in fields such as; Business, Education, Psychology and Mass Media. He also has taught many (online and in-site) courses to students from around the world in topics like Data Science, Mathematics, Statistics, R programming and Python. Alvaro Fuentes is a big Python fan and has been working with Python for about 4 years and uses it routinely for analyzing data and producing predictions. He also has used it in a couple of software projects. He is also a big R fan, and doesn't like the controversy between what is the “best” R or Python, he uses them both. He is also very interested in the Spark approach to Big Data, and likes the way it simplifies complicated things. He is not a software engineer or a developer but is generally interested in web technologies. He also has technical skills in R programming, Spark, SQL (PostgreSQL), MS Excel, machine learning, statistical analysis, econometrics, mathematical modeling

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Location

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Online

Start date

Different dates availableEnrolment now open

About this course

Learn about the most important libraries for doing Data Science with Python and how they can be easily installed with the Anaconda distribution
Understand the basics of Numpy which is the foundation of all the other analytical tools in Python
Produce informative, useful and beautiful visualizations for analyzing data
Analyze, answer questions and derive conclusions from real world data sets using the Pandas library
Perform common statistical calculations and use the results to reach conclusions about the data
Learn how to build predictive models and understand the principles of Predictive Analytics

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Computing
  • Statistics
  • Syntax
  • Mathematics
  • Simulation
  • Programming
  • Install
  • GCSE Mathematics
  • Programming Application
  • Database

Course programme

The Anaconda Distribution and the Jupyter Notebook 4 lectures 33:50 The Course Overview This video provides an overview of the entire course. The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
The Anaconda Distribution and the Jupyter Notebook 4 lectures 33:50 The Course Overview This video provides an overview of the entire course. The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. This video provides an overview of the entire course. This video provides an overview of the entire course. The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
The Anaconda Distribution Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
  • Explain what Anaconda Distribution is and the problem it solves
  • Go to the website to get Anaconda
  • Go through the steps of installing the software
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Introduction to the Jupyter Notebook Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Introduce the computing environment in which we will work for the rest of the course.
  • Explain what the Jupyter Notebook is
  • How to start the Jupyter Notebook from the command line?
  • Take a tour to see the interface of Jupyter
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Using the Jupyter Notebook Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
  • Using Jupyter Notebook to run regular Python statements
  • Explain the most important markdown syntax used in Jupyter
  • Show some of the most useful keyboard shortcuts
Vectorizing Operations with NumPy 3 lectures 43:10 NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Vectorizing Operations with NumPy. 3 lectures 43:10 NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy: Python’s Vectorization Solution Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
Explain what Numpy is, the problem it solves and why it is important for Python’s Data Stack.
  • Explain what Numpy is
  • Explain the problem Numpy solves
  • Give a motivating example to introduce Numpy
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
NumPy Arrays: Creation, Methods and Attributes Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
Introduce arrays, the main objects in Numpy, and how to create and use them.
  • Explain the different ways to create arrays
  • Show how to do mathematics with arrays
  • Show how to perform common manipulations: indexing, slicing and reshaping
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Using NumPy for Simulations Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Introduce with an example one of the common uses of Numpy: doing simulations.
  • Perform a simple simulation example: coin flips
  • Calculate descriptive statistics in the simulation results
  • Show how to perform a simulation of a stock price
Introduce with an example one of the common uses of Numpy: doing simulations...

Additional information

Python’s tools for doing Data Science

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Become a Python Data Analyst

£ 150 VAT inc.

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