Watch Become a Python Data Analyst
- 2017
- 1 Season
Become a Python Data Analyst is a comprehensive course provided by Packt Publishing that aims to provide learners with the necessary skills and knowledge to become a competent data analyst using the Python programming language. The course is suited for anyone who is interested in unlocking human insights from data and making informed decisions from it.
The course covers a range of topics, starting with the basics of Python, such as variables, functions, and data types, to advanced topics like data science concepts, data visualization, and machine learning models. Each section of the course is designed to help learners in a step-by-step manner, ensuring that they understand and can apply each topic effectively.
The course comprises over 11 hours of video lectures, wherein each video offers an interactive and engaging way of learning. The course instructor, Boris Paskhaver, is an experienced data scientist and engineer with over 10 years of professional experience in the field. He provides clear and concise explanations, making even the most complex topics easy to understand.
The first section of the course teaches the basics of Python programming language. It covers topics such as variables, functions, loops, and data structures that are essential for data analysis. Even beginners can understand these concepts with ease, and the instructor provides real-world examples to help students understand how to apply these concepts in real-life scenarios.
The second section of the course is dedicated to data analytics. It covers topics such as data cleaning, data manipulation, and data aggregation using Python. It also covers Pandas, which is a powerful library in Python used for data manipulation and analysis. Here, learners also learn how to work with structured data and how to get data from various sources, including Excel files, CSV files, and SQL databases.
The third section of the course is Data Visualization. Here, learners learn how to display and communicate insights from data through charts, tables, and other visual tools. The section covers popular Python libraries used for data visualization, such as Matplotlib, Plotly, and Seaborn. The instructor demonstrates how to use these libraries to create different types of visualizations, such as scatter plots, bar charts, and heatmaps.
The fourth section of the course is Machine Learning Basics, which teaches learners how to build predictive models using Python. The section covers topics such as supervised learning, unsupervised learning, and evaluation metrics. It also includes a hands-on exercise that demonstrates how to build a machine learning model using the Scikit-learn library.
The fifth and final section of the course is Practical Applications, which combines the knowledge and skills learned in the previous sections. Here, learners are presented with real-world data analysis problems and are taught how to solve them using Python. The section covers topics such as sentiment analysis, customer segmentation, and fraud detection.
Throughout the course, learners have access to practical exercises and quizzes that help to reinforce their understanding of the material. The course also includes a GitHub repository, which contains all the Python scripts used in the course, making it easy to follow along with the instructor.
In conclusion, Become a Python Data Analyst is a practical and comprehensive course that equips learners with the necessary skills and knowledge to become competent data analysts using Python. The course is designed to take learners on a journey from the basics of programming to advanced data analysis concepts, and it is suitable for beginners and intermediates alike. With the guidance of an experienced instructor, learners can confidently gain key skills in data analysis and machine learning.
Become a Python Data Analyst is a series that ran for 1 seasons (25 episodes) between May 30, 2017 and on Packt Publishing