Data Analytics Course

STATISTICAL MODELLING, TOOLS AND VISUALIZATION TO EXTRACT INFORMATION FROM DATA

Cedlearn Data Analytics has been around for ages. However, with the new tools, methods and prominence of Data Science, it has come into the limelight. With the ever-increasing volume of data and interest among the organization to extract information, there has been increasing demand for Data Analytics. Learn all the required tools and techniques with no coding.

Course Content:

1. Introduction to Data Analytics:

   • Understanding the basics of data analytics.
   • Different types of data (structured, unstructured, semi-structured).
   • Introduction to tools and technologies used in data analytics (e.g., Python, R, SQL, Excel).

2. Data Collection and Cleaning:

   • Methods for collecting data from various sources (databases, APIs, web scraping).
   • Data cleaning techniques to handle missing values, outliers, and inconsistencies.

3. Data Exploration and Visualization:

   • Exploratory data analysis (EDA) techniques.
   • Visualization tools and libraries (e.g., Matplotlib, Seaborn, Tableau).
   • Creating meaningful visualizations to uncover patterns and trends in data.

4. Statistical Analysis:

   • Basic statistical concepts (mean, median, mode, standard deviation, etc.).
   • Hypothesis testing and confidence intervals.
   • Regression analysis and correlation.

5. Machine Learning Basics:

   • Introduction to machine learning algorithms (supervised, unsupervised, and reinforcement learning).
   • Model evaluation and validation techniques.
   • Feature engineering and selection.

   • Benefits and Uses:

     1. Informed Decision Making:

        • Data analytics helps organizations make informed decisions based on data-driven insights rather than intuition or guesswork.

     2. Improved Efficiency:

        • By analyzing data, organizations can identify inefficiencies in processes and optimize resource allocation for better efficiency.

     3. Competitive Advantage:

        • Companies that effectively utilize data analytics gain a competitive edge by identifying market trends, customer preferences, and areas for innovation.

     4. Better Targeting and Personalization:

        • Data analytics enables businesses to target the right audience with personalized marketing campaigns, leading to higher conversion rates and customer satisfaction.

     5. Risk Management:

        • Analyzing historical data helps organizations identify potential risks and develop strategies to mitigate them, whether it's financial risks, operational risks, or cybersecurity threats.

        • Informed Decision Making: Data analytics provides the foundation for making informed decisions based on evidence rather than intuition. By analyzing data, organizations can identify trends, patterns, and insights that inform strategic decisions.

        • Competitive Advantage: In today's data-driven world, organizations that leverage data analytics effectively gain a competitive edge. By understanding customer behavior, market trends, and operational efficiencies, businesses can outperform competitors and adapt to changing market conditions more swiftly.

        • Improved Efficiency: Data analytics enables organizations to streamline processes, optimize resource allocation, and identify areas for improvement. By analyzing operational data, companies can eliminate bottlenecks, reduce waste, and enhance productivity.

        • Risk Management: Data analytics plays a crucial role in identifying and mitigating risks across various domains. Whether it's financial risks, operational risks, or cybersecurity threats, analyzing data allows organizations to proactively manage risks and prevent potential disruptions.

        • Enhanced Customer Experience: By analyzing customer data, organizations can gain insights into customer preferences, behaviors, and satisfaction levels. This information allows companies to tailor products, services, and marketing strategies to meet the needs of their target audience more effectively, leading to improved customer experiences and loyalty.

        •