Data Science
Completed by Farida Abbasova on July 3, 2025
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Data Science
Learning objectives
- Apply data analytics to real-world business challenges using appropriate analytic tools.
- Perform data cleaning, manipulation, and exploratory data analysis using Python libraries such as Pandas and Numpy.
- Build and evaluate machine learning models to predict trends and derive insights from data.
- Understand the role and applications of data science in uncovering patterns and making data-driven decisions.
Skills learned
- Machine Learning Methods
- Exploratory Data Analysis
- Predictive Analytics
- Data Visualization Software
- Marketing Analytics
- Business Analytics
- Digital Transformation
- Statistical Methods
- Artificial Intelligence
- Analytical Skills
- Predictive Modeling
- Data Presentation
- Data Wrangling
- Python Programming
- Deep Learning
- Regression Analysis
- Feature Engineering
- Data Mining
- Big Data
- Data Collection
- Business Logic
- Machine Learning
- Data Cleansing
- Data Manipulation
- Infographics
- NumPy
- Cloud Computing
- Data Science
- Statistical Analysis
- Data Storytelling
- Data Visualization
- Data Quality
- Analytics
- Data Analysis
- Scikit Learn (Machine Learning Library)
- Pandas (Python Package)
- Data-Driven Decision-Making
- Skills section collapsed. Showing 8 of 37 skills.
Learning content completed
Some of the content and skills presented have been contributed by the content provider.