The course provides the complete preparation you need to become a data analyst
Study mathematics for Python
Learn how to obtain interesting, real-time information from an API with a simple script
Go through a complete loan data case study and apply your NumPy skills
Practice with real-world data
Learn beginner and advanced Python
Understand different data types and their memory usage
Expand your knowledge of NumPy – statistics and preprocessing
Engage with coding exercises that will prepare you for the job
Acquire a big picture understanding of the data analyst role
Be able to work with text files
Complete a data cleaning exercise on absenteeism rate
Learn how to create pie, bar, line, area, histogram, scatter, regression, and combo charts
Fill up your resume with in-demand data skills: Python programming, NumPy, pandas, data preparation - data collection, data cleaning, data preprocessing, data visualization; data analysis, data analytics
We will teach you NumPy and pandas, basics and advanced
Clean data with pandas Series and DataFrames
Master data visualization
Solve a final capstone project
Most data analyst, data science, and coding courses miss a critical practical step. They don’t 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.
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