Data Analytics Essentials Using Python - 6 Sessions (Every Mon, Tue, Thu)

For more information: https://casugol.com/course/dae

International Acclaimed Certification. 5-Star Reviews

Suitable for everyone. Learn in an Interactive, Supportive, and Encouraging Environment.

• Duration: 3 Days / 24 Hours
• Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination

Course Objective

• Acquire the essential knowledge and technical skills on how data analytics can be used by organizations to enhance decision making and uncover hidden data insights.
• Learn the core components of Data Analytics, Data Preprocessing and Cleaning, Data Mining, Data Warehousing and Visualization using Python Programming.

Examination

• Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Artificial Intelligence, Machine Learning, and Python Programming based on the syllabus covered
• Participants are expected to score a minimum of 70% to pass the examination

MODULE 1 - INTRODUCTION TO DATA ANALYTICS

• Data Analytics Overview
• Concepts of Data Analytics
• Importance and Advantages of Data Analytics
• Developing / Application of Data Analytics Strategies
• Data Analytics Maturity Model
• Understanding Descriptive, Predictive and Prescriptive Analytics

MODULE 2 - DIFFERENT TYPES OF ANALYTICS AND APPLICATION

• Different Application of Analytics Method
• Concepts of Text Analytics and Web Analytics
• Data / information architecture
• ETL Architecture
• What is Data Warehouse
• Business intelligence vs Data Analytics
• Application of Analytics in an Organisation

MODULE 3 - DEEP DIVE INTO PYTHON PROGRAMMING

• Introduction to Python Programming
• Setting up Python IDE and Programming Environment
• Understanding Structure of Python Programming
• Python Variables: Integer, Floats, Strings
• Using of List vs. Dictionary
• Operators and Loops: If-Else, For, While, Break, Continue
• Types of Functions in Python
• Introduction to Built-In Functions in Python

MODULE 4 - WORKING WITH KEY MODULES / PACKAGES IN PYTHON FOR DATA ANALYTICS

• Understanding Modules in Python
• Working with NumPy Module
• Using Python Pandas Module
• Data Pre-processing, Data Cleaning, and Data Engineering
• Introduction to MatPlotLib in Python
• Data Visualization using Python Programming

MODULE 5 - DATA MINING PROCESSES FOR DATA ANALYTICS

• Fundamentals of Data Mining
• Objectives of Data Mining
• Key aspects of Data Mining
• Concepts of Knowledge Discovery in Databases (KDD)
• Models in Data Mining
• Data Mining Model vs Statistical Model
• Data Mining Processes

MODULE 6 - DATA MINING TECHNIQUES

• Different Data Mining Techniques
• Data Classification
• Clustering Analysis
• Regression Analysis
• Association Rules
• Outliers Analysis
• Sequential Patterns
• Predictive Analytics

MODULE 7 - DEEP DIVE INTO VISUALIZATION WITH PYTHON

• Data Visualization and Data Exploration
• Comparison Plots (Line Chart, Bar Chart, Radar Chart)
• Relation Plots (Scatter Plot, Bubble Plot, Correlogram, Heatmap)
• Composition Plots (Pie Chart, Stacked Bar Chart, Stacked Area Chart)
• Distribution Plots (Histogram, Density Plot, Box Plot, Violin Plot)
• Geo Plots (Dot Map, Choropleth Map, Connection Map)
• Enhancement of Visualization

MODULE 8 - MATPLOTLIB AND SEABORN LIBRARIES IN PYTHON FOR VISUALIZATION

• Deep Dive into Matplotlib in Python
• Essential Matplotlib Components for Plotting
• Basic Plots, Layouts, Images, and Mathematical Expressions using Matplotlib
• Introduction to Seaborn in Python
• Kernel Density Estimation, Bivariate Distribution, Pairwise Relationships
• Multi-plots, Regression Plots, Squarify, and Geospatial Plotting using Seaborn

MODULE 9 - UNDERSTANDING MACHINE LEARNING

• Statistical Learning vs. Machine Learning
• Iteration and Evaluation
• Supervised, Unsupervised, and Reinforcement Learning
• Different Phases of Predictive Modelling (Data Pre-processing, Sampling, Model Building, Validating)

Data Analytics Essentials (DAE) involves immersive hands-on experiences, thorough utilization of real-world case studies, practical exercises, and collaborative group discussions.

Be Recognized as a CASUGOL Certified Professional

Add Value to your already prolific portfolio with a Certificate of Competency from CASUGOL.

Awarded upon completing and meeting all requirements of the course.