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Power Bi

Power BI
Power BI is like a magician for your data, transforming dull spreadsheets into captivating visual stories. With its wizardry, you can weave together insights from various sources, unleashing the true power of your information. Imagine your data dancing in vibrant charts, graphs, and dashboards, telling a compelling tale that captivates your audience. Power BI doesn’t just analyse numbers; it breathes life into them, turning mundane statistics into a dynamic performance. It’s the storyteller in the world of data, where every click unveils a new chapter of discovery. In the realm of business intelligence, Power BI is the enchanting spell that turns data complexity into clarity, making you the master of a visual narrative that speaks volumes.

What Power BI is used for?

Power BI is a powerful business analytics tool by Microsoft, used for transforming raw data into interactive visualizations and business intelligence insights. It enables users to connect to various data sources, create compelling reports and dashboards, and share them across organizations. With features like data modeling, real-time analytics, and cloud integration, Power BI aids in informed decision-making. It is employed across industries for data-driven decision support, performance tracking, and gaining actionable insights, making it an essential tool for professionals seeking efficient data visualization and analysis in today’s competitive business landscape.

Data Visualization

  • Bar Chart
  • Histogram
  • Box whisker plot
  • Line plot
  • Scatter Plot
  • Heat Map
  • Matplotlib, Seaboarn– Visualization.

Regression (Supervised Learning)

  • What is regression?
  • Use Cases: Regression
  • Linear Regression
  • Theory behind Linear Regression
  • Model Evaluation and related metrics
  • Root Mean Square Error (RMSE)
  • R-Square,
  • Adj R-Square
  • Feature selection methods
  • Linear regression – Practice Problem.

Overfitting/Under fitting

  • Understand what is overfitting and under fitting model
  • Visualize the overfitting and under fitting model
  • How do you handle overfitting?

Decision Trees

  • What are Decision Trees?
  • Gini, Entropy criterions
  • Decision trees in Classification,/li>
  • Decision trees in Regression
  • Ensembles
  • Random Forest
  • Boosting (Ada, Gradient, Extreme Gradient),/li.
  • SVM

Re-sampling Techniques

  • K-fold
  • Repeated Hold-out Data
  • Bootstrap aggregation sampling.

Tree Based Algorithms

  • Gini Index
  • Entropy
  • Information Gain

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    Frequently Asked Question

    AI in data science automates complex tasks like pattern recognition and predictive modeling. Machine learning algorithms analyze vast datasets to uncover insights, make predictions, and optimize decision-making. AI enhances data processing efficiency, enables advanced analytics, and supports data-driven decision-making, revolutionizing the field of data science.

    In general programming, we have the data and the logic by using these two we create the answers. But in machine learning, we have the data and the answers and we let the machine learn the logic from them so, that the same logic can be used to answer the questions which will be faced in the future. Also, there are times when writing logic in codes is not possible so, at those times machine learning becomes a saviour and learns the logic itself

    "With our data science course, you'll master essential skills in Python, power BI and machine learning. Analyse data, create insightful visualizations, and apply statistical techniques. Gain hands-on experience with real-world projects, fostering critical problem-solving skills. Acquire the knowledge to excel in diverse data-driven roles and drive innovation in any industry.

    Python is known for its simplicity, readability, and versatility. It supports object-oriented, imperative, and functional programming styles. Its extensive standard library facilitates diverse tasks. Dynamic typing and automatic memory management enhance development speed. Python is widely used for web development, data science, machine learning, and automation.

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