Star Certification in Big Data Analytics
With the advance of IT storage, processing, computation, and sensing technologies, Big Data has become a novel norm Of life. Only until recently, computers are able to capture and analysis all sorts of large-scale data from all kinds of fields people, behavior, information, devices, Sensors, biological signals, finance, vehicles, astrology, neurology etc. Almost all industries are bracing into the challenge of Big Data and want to big out valuable information to get insight to solve their challenges. Data Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us understand our world better, and in many contexts, enable us to make better decisions.
Beginner to Advance, Learner should have basic Knowledge of Statistics and Mathematics or Learners should be from Finance background.
Big Data Analytics Course Objectives:
- Big Data and how the same impact the business.
- Analyzing the data using the programming and Visualization tools.
- Different Data Mining techniques and how to use the same in your daily operations.
- Different Analytical techniques and their usage in multiple industries.
- Describe Big Data and Its Importance
- Analyze the unstructured data and apply R Programming Concepts on it.
- Describe the Big Data usage in different Industries
- Implement Machine Learning concepts and Data Visualization techniques on data.
- Work as Data Analyst and can generate prediction based on the analyzed data.
Table Of Contents Outline:
Part 1: Exploring Big Data and Hadoop
1. Introducing Data and Big Data
2. Big Data and Hadoop
Part 2: Analyzing Big Data with R
1. Exploring Analytics
2. Exploring R- Data Analytics language
3. Performing Statistics concepts with R
Part 3: Exploring Machine Learning
1. Introduction to Machine Learning
2. Machine Learning and Hadoop
Part 4: Big Data and Data Mining
1. Retrieving Text and Search Engines
2. Text Mining and Analytics
3. Pattern Discovery in Data Mining
4. Analyzing Clusters in Data Mining
Part 5: Big Data and Data Visualization
1. Data Visualizations and Tools
Part 6: Exploring Mobile analytics
Part 7: Big Data in different Industries
Part 8: Exploring Real World Analytical Organizations
Part 9: Lab Exercises