Data Analytics

Data analytics is a strategy-based science that involves analyzing raw data to find trends, answer questions, and draw conclusions. It uses tools and processes to combine and examine datasets to identify patterns and develop actionable insights.

Course Advantages:

• Global Certificate
• Latest Syllabus and Advanced Lab Facility
• Provide hands-on experience with popular tools and programming languages such as Python,SQL, and data visualization tools like Power BI.

Course Features:

• Data analytics is a high-demand skill in various industries. Completing a data analytics course makes you valuable to employers seeking professionals with the ability to derive insights from data.
• Data analytics skills open up a wide range of career opportunities in fields such as business, finance, healthcare, marketing, and technology. Many organizations are actively seeking professionals who can analyze and interpret data.
• Organizations that leverage data analytics gain a competitive advantage. Individuals with data analytics skills contribute to this advantage by helping their employers stay ahead in a data-driven business landscape.

What You'll Cover In This Course:

• Data Basics
• Topic
• Define the Concept of Data
• Describe Basic Data Variable Types
• Describe Basic Structure used in Data Analytics
• Describe Data Categories
• Data Manipulation
• Topic
• Import,Store,and Export Data
• Clean Data
• Organize Data
• Aggregate Data
• Data Analysis
• Topic
• Describe and Differentiate Between Types of Data Analysis
• Describe and Differentiate Between Data Aggregation and Interpretation Metrics
• Describe and Differentiate Between Exploratory Data Analysis Methods
• Evaluate and Explain the Results of Data Analyses
• Define and Describe the Role of Artificial Intelligence in Data Analysis
• Data Visualization and Communication
• Topic
• Report Data
• Create Visualozations from Data
• Derive Conclusions from a Data Visualization
• Responsible Analytics Practices
• Topic
• Describe Data Privacy Laws and Best Practices
• Describe Best Practices for Responsible Data Handling
• Given a Scenario, Describe Types of Bias that Affect Collection and Interpretation of Data