Alpha Net Consulting Lead Software Interview Questions and Answers

1st round was Aptitude, which is average difficultly level.

2nd round was Group Discussions, here they only check our communication.

Q1. Techincal Round, here the technical questions about our bachgroud were asked. They will ask questions based on our resume.
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Q2. What is Artificial Intelligence?
Ans. 
Artificial Intelligence is the simulation of human intelligence processes by machines, especially computer systems.
• AI involves machines performing tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

• Machine learning is a subset of AI that enables machines to learn from data and improve their performance over time.

• Examples of AI applic...read more
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Q3. What is Power BI?
Ans. 
Power BI is a business analytics tool by Microsoft that provides interactive visualizations and business intelligence capabilities.
• Power BI is a data visualization tool used to create interactive reports and dashboards.

• It allows users to connect to various data sources, clean and transform data, and create visually appealing reports.

• Power BI offers a wide range of visualization options such as charts, graphs, maps, and...read more
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Q4. How to load Data in Power BI?
Ans. 
Data can be loaded in Power BI by connecting to various data sources like Excel, SQL databases, online services, etc.
• Connect to data sources by clicking on 'Get Data' in Power BI

• Select the desired data source (e.g. Excel, SQL Server, SharePoint, etc.)

• Choose the specific data tables or queries to import into Power BI

• Transform and clean the data using Power Query Editor if needed

• Load the data into Power BI model for visu
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Q5. Explain about your final year project?
Ans. 
Developed a predictive analytics model for predicting customer churn in a telecom company.
• Used machine learning algorithms like logistic regression and random forest for analysis.

• Performed data preprocessing, feature engineering, and model evaluation.

• Achieved an accuracy of 85% in predicting customer churn.

• Presented findings and recommendations to the telecom company's management team.
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