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    Data Analytics Course

    BY
    IBM , IIT Roorkee via Intellipaat

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    Mode

    Online

    Fees

    ₹ 85044

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study, Virtual Classroom
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 85,044

    The fees for the course Data Analytics Course is -

    HeadAmount in INR
    Programme FeesRs. 85,044

     

    certificate availability

    Yes

    The syllabus

    Getting Started with Foundations of Data Analytics

    Diving into Structured Query Language (SQL) for Data Management
    • Gain a basic understanding of SQL, including the Entity Relationship Model (ERM) and database normalization concepts
    • Elaborate SQL operators and demonstrate operations such as joins and subqueries
    • Learn how to use stored procedures, views, and SQL functions to manipulate and retrieve data efficiently
    • Explain SQL optimization strategies to improve performance and manage database concurrency to maintain data integrity, consistency, and isolation
    Explore Python Programming Language for Data Analysis and Visualization
    • Exploring the basics of Python programming and how to set up IDEs. Also, understand the fundamental concepts of Python, such as syntax, data types, operators, and control structures
    • Grasping the Object-Oriented Programming (OOP) concepts, including classes, objects, inheritance, and polymorphism
    • Acquire practical experience with data manipulation using Python libraries such as NumPy and Pandas and learn to visualize data
    Applying Essential Concepts of Statistics And Probability
    • Learn the concepts of Descriptive Statistics, covering measures of Central Tendency, Dispersion, and Data Visualization Techniques, and understanding the application of probability for decision-making and statistical modeling
    • Dive into Inferential Advanced Statistics, including hypothesis testing and confidence intervals

    Learn Machine Learning Algorithms and Advanced Analytics Techniques

    Diving into Core Concepts of Machine Learning
    • Understanding Fundamental of Machine Learning Concepts: Supervised and Unsupervised Learning, Model Evaluation, Clustering algorithms, and Feature Engineering
    • Learn Regression and its types (linear, logistic, and polynomial regression)
    • Explore Classification Algorithms, covering Decision Trees, Support Vector Machines, and Neural Networks
    Examine Performance Metrics in Machine Learning
    • Learn how to develop Classification reports using metrics such as Precision, Recall, Accuracy, Macro average, and Weighted Average
    • Describe how to Use the Confusion Matrix for Model Evaluation and Monitoring
    Applying Advanced Techniques in Time Series Forecasting
    • Performing time series data analysis, gathering insights and practical forecasting solutions using time series forecasting

    Implementing Real-world Business Applications, Case Studies, and Capstone Projects

    Exploring Business Applications, Case Studies, and Capstone Projects
    • Grasp different business domains such as finance, marketing, retail, and supply chain and articulate their distinct functions
    • Gain knowledge about formulating hypotheses for numerous business problems on samples and populations
    • Study about exploratory data analysis (EDA) and how it facilitates the foolproof production of actionable insights
    • Study how to narrate business problems and solutions in a simple, relatable format that makes them easier to understand, grasp, and recall
    • Develop actionable insights from raw, unstructured data to deploy real-world business solutions
    Building Data Analytics Capstone Project
    • Define the problem statement and project objectives to contrast the scope of the data analytics capstone project. Alongside, build an approach to solving the problem by implementing optimal solutions using data analysis and modeling techniques
    • Use evaluation metrics and actionable insights to assess the performance of the optimal solutions
    Explore the Real-Time Business Case Studies
    • In this case study on Customer churn, you will be using predictive modeling to find the causes of customer attrition to enhance customer retention
    • This case study on sales forecasting uses statistical methods and predictive analytics. It implements historical data and statistical techniques to predict future sales trends for better decision-making
    • Using Census Data for Demographic Insights, this case study analyzes demographic data to guide product development and targeted marketing strategies
    • This case study on predictive modeling focuses on real-world scenarios to improve decision-making and operational efficiency
    • This case study on HR Analytics uses workforce data to forecast turnover and improve recruitment and performance tactics
    • This case study on dimensionality reduction techniques illustrates the use of methods such as PCA to streamline datasets, improving model performance and efficiency
    • In this housing price prediction case study, implement statistical methods to predict real estate prices based on affecting factors
    • This case study on customer segmentation focuses on finding various customer segments for customized marketing and better experiences
    • In this inventory management case study, you will be using analytics to optimize inventory stocks, reduce capex and opex, and ensure product availability
    • In this case study on disease prediction, you will be implementing machine learning on patient data to analyze disease occurrence and take the necessary steps.

    Elective

    Learn Microsoft Excel for Data Analysis and Visualization
    • Mastering Excel For Data Analytics, Visualization, and VBA macros for automation
    • Explore the methods for ensuring data and file security
    Visualizations using Power BI
    • Demonstrate Data Visualization and Analytics with Power BI for Managing Reports and Dashboards
    • Explore real-time applications of DAX in developing reports and dashboards
    Job Readiness Training and Support Program
    • Learning Job Search Strategies to establish networking and interview skills
    • Learn how to build an effective resume and manage a LinkedIn profile
    • Interview Preparation and Mock Interview Sessions Led by Industry Professionals
    • Placement opportunities with 400+ hiring partners upon passing the Placement Readiness Test (PRT)

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