Data Analytics Course

IBM , IIT Roorkee via Intellipaat

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                                    Medium of instructions
                                    English

                                    Mode of learning
                                    Self study, Virtual Classroom

                                    Mode of Delivery
                                    Video and Text Based

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

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

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

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

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

Performing time series data analysis, gathering insights and practical forecasting solutions using time series forecasting

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

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

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.

Mastering Excel For Data Analytics, Visualization, and VBA macros for automation
Explore the methods for ensuring data and file security

Demonstrate Data Visualization and Analytics with Power BI for Managing Reports and Dashboards
Explore real-time applications of DAX in developing reports and dashboards

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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