Advanced Data Analysis Techniques
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Course Details
Introduction
Objective
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In a data-rich world, you will not stand out in the crowd with raw data; it’s the interpretation, exploitation, and analysis that make a significant impact. To unleash business intelligence, create innovation, and make informed decisions faster, advanced analytics expertise goes from nice to a necessity.
LPC Training's Advanced Data Analysis Techniques training program is a practitioner-level, five-day training that equips professionals to work with current data science and visualization methodologies and tools. Using interactive examples and exercises drawn from practice and the real world, you will become competent in machine learning, time series prediction, natural language processing (NLP), Bayesian inference, and big data analysis with Python, Spark MLlib, and Scikit-learn, and more.
At the end of this course, you will not only be able to work with big data proficiently, but you will also be able to extract key insights and be capable of communicate these in clear and effective ways.
Course Outline
Exploratory Data Analysis
- Definition of exploratory data analysis (EDA) and its importance in data analysis
- Introduction to Python for data analysis and its basic syntax
- Techniques for data visualization and exploration using Python libraries
- Examining Python’s central tendency, dispersion, and correlation measures
- Discussing outlier detection and treatment methods using Python
- Exercise: Configuring Python environment and using Python libraries to visualize and explore data
