Data Analysis & Visualization: Python | Excel | BI | Tableau

Data Analysis & Visualization: EXCEL | SQL AND PYTHON

Data analysis is the process of inspecting, cleaning, transforming, and modeling data in order to extract useful information, draw conclusions, and support decision-making. It involves using statistical and computational methods to identify patterns, relationships, and trends in data, and then communicating those findings in a clear and meaningful way.

Data analysis can be applied to a wide variety of data types, including numerical, categorical, and textual data. It is used in many fields, such as business, science, engineering, medicine, and social sciences, to gain insights from data and make informed decisions based on those insights.

The process of data analysis typically involves several stages, including:

Data collection: Collecting and acquiring data from various sources.

Data cleaning: Preparing and cleaning the data by removing any errors, duplicates, or missing values.

Data exploration: Examining the data to identify patterns, outliers, and relationships between variables.

Data modeling: Developing mathematical models or algorithms to analyse the data.

Data visualization: Creating charts, graphs, and other visualizations to help communicate the insights gained from the analysis.

Interpretation and communication: Drawing conclusions from the analysis and presenting the findings in a clear and understandable way to stakeholders.

IN summary:

What you'll learn

·        A Beginner's Guide to Microsoft Excel - Microsoft Excel, Learn Excel, Spreadsheets, Formulas, Shortcuts, Macros

·        Become proficient in Excel data tools like Sorting, Filtering, Data validations and Data importing

·        Master Excel's most popular lookup functions such as Vlookup, Hlookup, Index and Match

·        Make great presentations using Bar charts, Scatter Plots, Histograms etc.

·        Knowledge of all the essential SQL commands

·        Become proficient in SQL tools like GROUP BY, JOINS and Subqueries

·        Become competent in using sorting and filtering commands in SQL

·        Learn how to solve real life problem using the Linear Regression technique

·        Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem

·        Understand how to interpret the result of Linear Regression model and translate them into actionable insight

·        Macros

·        Importing Data from External Sources

·        SQL Introduction

·        Installation and Getting Started

·        Database Basics and advanced

·        SQL Statements

·        Restore and Backups

·        Mathematical functions

·        Setting up and using Python and Jupyter Notebook for data analysis

·        Machine Learning

·        Data Processing

·        Linear Regression

PROJECT MANAGEMENT

Course Description:

This course provides an in-depth introduction to the fundamental principles and practices of project management. Participants will gain a comprehensive understanding of the project management life cycle, key concepts, tools, and techniques necessary to successfully plan, execute, monitor, and close projects. Through a combination of theoretical knowledge and practical exercises, students will develop the skills required to manage projects effectively and efficiently.

Course Objectives:

By the end of this course, student will be able to:

Define and understand the key concepts, terminologies, and principles of project management.

Develop a project charter and project plan that outlines scope, schedule, budget, and resource requirements.

Identify and manage project stakeholders.

Create a Work Breakdown Structure (WBS) and define project tasks.

Estimate project costs and create a project budget.

Develop a project schedule using critical path analysis.

Implement risk management strategies and monitor project risks.

Identify and manage project changes and issues.

Monitor project progress and performance.

Use project management software and tools to aid in project planning and tracking.

Understand the importance of team dynamics and leadership in project management.

Prepare and present project reports and communicate effectively with project stakeholders.

Close out projects and conduct post-project evaluations.

Course Outline:

Module 1: Introduction to Project Management

What is Project Management?

Key Terminologies and Concepts

Importance of Project Management

Project Life Cycle

Module 2: Initiating a Project

 Project Charter

Stakeholder Identification and Analysis

Project Objectives and Scope Definition

Module 3: Planning and Scheduling

Work Breakdown Structure (WBS)

Estimating Project Costs

Developing a Project Budget

Creating a Project Schedule

Critical Path Analysis

Module 4: Risk Management

Identifying and Analyzing Project Risks

Risk Mitigation and Response Planning

Risk Monitoring and Control

Module 5: Executing and Controlling a Project

Managing Project Teams

Project Communication and Reporting

Change Management

Issue Identification and Resolution

Module 6: Closing a Project

 Project Closure Activities

Post-Project Evaluation and Lessons Learned

Final Project Reports and Documentation

Course Review and Assessment

Assessment Methods:

Quizzes and Assignments: Regular quizzes and assignments to test understanding.

Final Project: Students will apply their knowledge by creating a project plan for a hypothetical project.

Final Exam: A comprehensive final exam covering all course topics.

Certificate is issued automatically at end of Training.

Duration: 1 month per course.

Lectures are once or twice a week. 2 hours per day. Some online classes may be scheduled as well . Some who prefer weekends are welcome.