Data Analytics Course

Categories: Development
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About Course

Data analytics is the complete process of analyzing raw data to uncover meaningful
insights, patterns, and trends that can assist many businesses in making informed
decisions. It may include the collection, processing, and analysis of data to extract
valuable information that can be used to make business strategies and boost
performance. We also provide best Data Analytics Course, which will give you a chance to learn quick and easy.

Why to go for a data analytics course?

A data analytics course usually covers various aspects of data analysis, including data
collection, cleaning, analysis, and visualization.

Course duration: 2 months.

Course outlines:

Week 1: Introduction to Data Analytics

● Importance of data analytics in decision-making
● Types of data analytics (descriptive, diagnostic, predictive, prescriptive)
● Data sources and types of data (structured, unstructured, semi-structured)
● Data collection methods (surveys, interviews, sensors, web scraping)
● Data cleaning and preprocessing techniques.

Week 2: Data Analysis Techniques

● Exploratory data analysis (EDA)
● Statistical analysis (descriptive statistics, inferential statistics)
● Data mining techniques (clustering, classification, regression, association)

Week 3: Data Visualization

● Principles of data visualization
● Types of data visualizations (bar charts, line charts, scatter plots, etc.)
● Tools for data visualization (Tableau, Power BI, Matplotlib, seaborn)
● Overview of machine learning
● Supervised learning vs. unsupervised learning
● Common machine learning algorithms (linear regression, logistic regression,
decision trees, k-means clustering, etc.)

Week 4: Big Data Analytics

● Introduction to big data
● Challenges and opportunities of big data analytics
● Technologies for big data analytics (Hadoop, Spark, etc.)

Week 5: Data Analytics Tools

● Introduction to data analytics tools (Excel, R, Python, SQL, etc.)
● Hands-on exercises using data analytics tools
● Data Analytics in Business
● Applications of data analytics in business (customer segmentation, churn
prediction, market basket analysis, etc.)
● Case studies of successful data analytics implementations in business.

Week 6: Ethical and Legal Considerations in Data Analytics

● Privacy concerns in data analytics
● Ethical considerations in data analysis
● Compliance with data protection regulations (GDPR, CCPA, etc.)

Week 7: Data Analytics Project

● Working on a data analytics project from start to finish
● Applying data analytics techniques to real-world data sets
● Presenting findings and recommendations based on data analysis.

Week 8: Data Analytics Trends and Future Outlook

● Emerging trends in data analytics (AI, machine learning, big data)
● Future of data analytics and its impact on various industries.

Venue & tutors:

The course will be held online by the mentors of Hawks International institute, at Hawks

What Will You Learn?

  • Informed decision-making: Empowers you to make data-driven decisions based on actionable insights.
  • Career advancement: Opens doors to lucrative job opportunities in various industries with high demand for data analysts.
  • Improved efficiency: Streamlines processes and operations by identifying inefficiencies and areas for optimization through data analysis.
  • Enhanced business intelligence: Provides valuable insights into market trends, customer behavior, and competitive landscape.
  • Competitive edge: Gives you a competitive advantage by leveraging data to drive innovation and stay ahead of competitors.
  • Strategic planning: Enables strategic planning and forecasting based on predictive analytics and trend analysis.

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