Data Analytics Using Python
As businesses increasingly rely on latest technology to solve business problems, data professionals today need exceptional quantitative skills and a high-level understanding of the models that are employed to solve challenges.
what you will learn
Course Overview
In this course, you will learn the importance of collecting, organizing and manipulating large amounts of data using the latest technologies. With this course, you will have complete understanding of working with data and analytics, and a hands-on knowledge of Python, such as Accessing Data from different services, processing data, data visualization, working with text data and managing time series data.
Course Modules
Accessing Data
- Accessing Data from Files
- Accessing Data from Relational Databases
- Accessing Data from Web pages
- Accessing Data from Web services
Processing Data
Python Libraries for Managing Data
- Introduction to NumPy
- Introduction to Pandas
Data formats
- Flattened Data
- Hierarchical Data - JSON, XML
- Binary Data
Cleaning and Transforming Data
- Data Aggregation
- Data Sorting and Filtering
- Finding and Fixing invalid values and removing duplicates
- Transforming values - Functions and Maps
Combining and Merging Data
Reshaping data
Data Visualization
- Charts
- Graphs
- Distributions
- Trends
- Geo-Data
- Specialized visualization - word clouds
Working with Text Data - Natural Language Processing
- Structure and Representation in Text
- Models for textual data - Bag of Words, N-grams
- Managing language structure - stemming, lemmatization, stopwords
- Application: Sentiment Analysis
Managing Time Series Data
Managing Dates and Times in Python
- Dates
- Times and Time Zones
Structure of Time Series Data - Indexing
Periods and Frequencies
Resampling Data from Time Series
Visualizing time series