Best Data Science Course in Kolkata for Freshers and Working Professionals.

 What is data science course eligibility?

To join data science course in Kolkata AEM Institute you must be a B.Tech, MCA or any graduate degree with computer science. It is always better to have a programming background like python or R to learn data science better. If you are working with Business Intelligence tools like Power BI then also you may consider our data science course in Kolkata for a better career option in 2024.
Professionals who have working experience in Data Analytics may also opt for our data science training program in Kolklata.

 Top Data Science Certification Training courses in Kolkata

• Data science is the backbone of today's technological advancements, driving decision-making, innovation, and insights across industries. Whether you're a beginner looking to enter the field or a seasoned professional aiming to upskill, our course has something for everyone. Learn to build a report or analyse data with Azure Cloud.
• In the era of big data, knowing how to handle large datasets is crucial. We'll dive into big data technologies such as Hadoop and Spark, teaching you how to process and analyze massive amounts of data efficiently. Learn Data Analytics with AWS Cloud.
• Machine learning is at the heart of data science. Our course will guide you through the intricacies of machine learning algorithms, helping you build predictive models and understand their real-world applications. Learn Machine Learning with AWS Cloud.

 Some Data Science Projects in Kolkata.

•  Customer Segmentation for E-Commerce: Analyze customer data from an e-commerce platform to identify distinct customer segments based on purchasing behavior, demographics, and preferences. Implement clustering algorithms to group customers, enabling personalized marketing strategies and targeted promotions.
•  Predictive Maintenance in Manufacturing:Utilize historical equipment data and machine sensor readings to predict when machinery is likely to fail. Implement machine learning models to forecast maintenance needs, reducing downtime and optimizing maintenance schedules for cost-effectiveness.
•  Financial Fraud Detection: Develop a fraud detection system for financial transactions using machine learning algorithms. Analyze transaction patterns, identify anomalies, and create a predictive model to detect potential fraudulent activities, enhancing the security and reliability of financial systems.
•  Healthcare Analytics: Patient Readmission Prediction: Analyze electronic health records to predict the likelihood of patient readmission. Implement predictive models to identify high-risk patients, allowing healthcare providers to intervene with personalized care plans and reduce hospital readmission rates.
•  Social Media Sentiment Analysis: Analyze social media data to understand public sentiment around a brand, product, or event. Use natural language processing techniques to classify social media posts as positive, negative, or neutral, providing valuable insights for reputation management and marketing strategies.
•  Churn Analysis for Subscription Services: Investigate customer churn for subscription-based services by analyzing user engagement data. Identify key factors contributing to churn, build a predictive model to forecast potential churners, and recommend targeted retention strategies to enhance customer loyalty.
•  Employee Performance Analysis: Evaluate employee performance within an organization by analyzing key performance indicators (KPIs) such as productivity, attendance, and project completion rates. Identify patterns and correlations to enhance HR decision-making and optimize workforce management.
•  Epidemiological Analysis: Disease Outbreak Prediction: Analyze public health data to predict and prevent disease outbreaks. Utilize historical health records, environmental factors, and demographic data to build models that forecast the likelihood of disease outbreaks, enabling proactive public health interventions.