Data Analyst

Students in Udacity’s Data Analyst course learn to clean up messy data, uncover patterns and insights, make predictions using machine learning, and clearly communicate their findings. To optimize the success of this program, students should be able to communicate fluently and professionally in written and spoken English and have a basic understanding of the prerequisites to help prepare for the curriculum.

The length of the program will depend on the time commitment, with an average of 3-4 months for completion. The price is based on a monthly subscription fee and reflects the course taking four months to finish.

Prerequisites
• Basic Python
• Basic descriptive statistics
• Pandas
• Data analysis process
• Basic SQL
• Inferential statistics
• Elementary algebra

What You’ll Learn
• Introduction to Data Analysis with Pandas and NumPy (Pandas, Exploratory data analysis, Basic data visualizations, Jupyter notebooks, Data storytelling, Data analysis process, NumPy, and Data manipulation)
• Advanced Data Wrangling (Data cleaning, Data storage, Data Tidiness Assessment, Data gathering, Pandas, Data quality assessment, Data wrangling, and File i/o)
• Data Visualization with Matplotlib and Seaborn (Latent variables, Data visualization design, Data fluency, Exploratory data analysis, Professional presentations, Data limitations and biases, Data storytelling, Jupyter notebooks, and Quantitative data visualization)