Certificate in Data Science for Smarter Problem Solving
-- ViewingNowThe Certificate in Data Science for Smarter Problem Solving is a comprehensive course designed to empower learners with essential data science skills for career advancement. In today's data-driven world, there is an increasing demand for professionals who can analyze, interpret, and apply data to solve complex problems.
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⢠Introduction to Data Science · Overview of the data science landscape, key concepts, and techniques.
⢠Data Wrangling · Cleaning, preprocessing, and transforming raw data for analysis.
⢠Data Exploration · Descriptive statistics and data visualization for data understanding.
⢠Statistical Analysis · Hypothesis testing, regression analysis, and probability theory.
⢠Machine Learning Fundamentals · Supervised, unsupervised, and reinforcement learning, model evaluation.
⢠Data Visualization · Interactive and static visualization techniques for storytelling and communication.
⢠Big Data Processing · Introduction to Hadoop, Spark, and NoSQL databases.
⢠Predictive Modeling · Building and deploying machine learning models for prediction and classification.
⢠Ethics in Data Science · Addressing ethical concerns, bias, and fairness in data and algorithms.
⢠Capstone Project · Applying course concepts to solve real-world data science problems.
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These professionals focus on extracting valuable insights from large, complex datasets using various techniques and tools. 2. **Data Analyst (25%)**
Data Analysts clean, transform, and interpret data, discovering trends and insights to drive business decisions. 3. **Data Engineer (20%)**
Data Engineers build and maintain architectures for processing, storing, and extracting data, ensuring systems can handle increasing data volume and complexity. 4. **BI Analyst (15%)**
BI Analysts create and maintain data reporting systems, enabling organizations to make informed decisions based on reliable, timely information. 5. **Data Visualization Specialist (10%)**
Data Visualization Specialists create visual representations of data to help organizations identify trends, patterns, and relationships, facilitating data-driven decision-making.
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