Factual Elite Programme in Data Science introduces both the theoretical foundation of Data Science Algorithms and their practical applications in R, Python, and Tableau. The amount and variety of data being generated in the world today are unprecedented. As this growth continues exponentially, companies must leverage insights buried beneath mountains of data. They need specially trained and highly skilled people who can turn endless streams of data into useful insight and actionable intelligence.

By attending this data science course, you’ll master data exploration, data visualization, descriptive analytics, sentiment analysis, time series analysis, and machine learning algorithms with R and Tableau. In this program, you’ll get hands-on practice by implementing various real-life, industry-based projects.

• Getting Started With R and Python Introduction to the basics of R and Python programming languages for data science.

• Exploratory Data Analysis Techniques to explore and summarize data for insights and patterns.

• Basic Statistics, Probability, and Hypothesis Testing Foundations of statistics, probability concepts, and hypothesis testing methods.

• Learning With Linear Classifier Introduction to linear classifiers for predictive modeling.

• Sentiment Analysis Analyzing text data to determine the sentiment behind it.

• Time Series Analysis Techniques to analyze data points collected or recorded at specific time intervals.

• Business Intelligence With Tableau Using Tableau to visualize data and create interactive dashboards.

• Unsupervised Machine Learning Techniques Exploring algorithms for clustering and pattern detection without labeled data.

• Supervised Machine Learning Techniques Learning algorithms for predictive modeling with labeled data.

• Bagging, Random Forest, and Boosting Advanced ensemble techniques to improve model accuracy and performance

• Revision, Exams, and Capstone Project Review of concepts, assessment through exams, and a comprehensive final project.

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