Let’s chat? - We're online
Greetings from Mazenet! Please share a few details about yourself.
Book a time slot
Book a time slot
Powered by Mazenet

Comprehensive Data Analysis Training Program To Become a Data Analyst Pro

Contact Us


Get Started Today

Objectives

This Data Analysis Training Course equips participants with skills in data analysis, visualization, statistical modeling, and machine learning.

Covering Python, SQL, R, Power BI, Tableau, AWS, and Azure, the course includes hands-on sessions for practical application. Learn to analyze complex datasets, create interactive dashboards, build predictive models, and manage data integration, driving data-driven decisions in your organization.

Course Outcome

Overview of Data Analysis Methodologies
Techniques for Independent Analysis of Large Datasets using Python and SQL
Data Visualization and Dashboard Development with Power BI
Statistical Modelling and Optimization with Python
Quantitative Analysis and Data Management with SQL
Advanced Data Visualization Techniques with Tableau
Predictive Modelling and Machine Learning with Python
Data Consolidation and Periodical Reporting with AWS
Cloud Concepts and Data Integration with Azure
Advanced Data Analysis Techniques with R
Get More Information
Contact Us
Ready to get started?
Let's chat.
info@mazenetsolution.com +91 7397723052
Get In Touch With Us


Get Started Today

Course Preview

  • Overview of data analysis methodologies
  • Techniques for independently analyzing large datasets.
  • Identifying trends, gaps, and patterns in complex data sets using Python and SQL

  • Principles of data visualization for supporting business objectives
  • Developing analytics dashboards, reports, and visualizations using Power BI
  • Hands-on session with Power BI for dashboard creation

  • Creating statistical and optimization frameworks using Python. Python libraries such as numpy, pandas, sklearn, pytorch, keras, and scipy.
  • Techniques for improving processes, products, or profits.
  • Hands-on session with Python libraries for statistical modelling.

  • Performing quantitative or statistical analysis using SQL
  • Data mining, data management, and data transformation techniques using SQL.
  • Hands-on session with SQL for data analysis and management

  • Advanced data visualization techniques for complex datasets using Tableau.
  • Incorporating interactivity and dynamic elements into visualizations
  • Hands-on session with Tableau for advanced visualization

  • Introduction to predictive modelling and machine learning concepts using Python.
  • Time series forecasting, clustering, classification, and regression using machine learning algorithms in Python.
  • Hands-on session with Python libraries for predictive modelling.

  • Analysing and consolidating data from various sources using AWS services
  • Producing periodical reports utilizing various data sources
  • Hands-on session with AWS for data consolidation and reporting

  • Introduction to cloud computing concepts with Azure
  • Integrating data from cloud and on-premises sources using Azure services
  • Hands-on session with Azure for data integration