Best Data Analytics Course Online 

Learning Outcomes

• Become proficient in using Excel for data cleaning, manipulation, and analysis.
• Master the use of formulas, functions, and pivot tables to analyze complex datasets.
• Develop a comprehensive understanding of advanced Excel techniques for data analysis.
• Learn how to visualize data and communicate insights effectively using Excel.

Topics Covered

• The Module 2 - Excel and Data Preparation module will be an introduction into the use of Excel for data analysis. It involves the techniques for data cleaning and preparation in Excel, which is an essential skill in data analysis. The module explains how to analyze data with different Formulas and functions in Excel and the utility of pivot tables and data visualization features within the application. The module concludes with a look into Advanced Excel techniques that provide a deeper exploration of data. Download Curriculum to Know the topics clearly. Download Curriculum to Know the topics clearly.

Learning Outcomes

• Understand the basics of SQL and relational databases and become proficient in writing SQL queries.
• Learn advanced SQL techniques, including joins, aggregations, and data cleaning/validation.
• Become familiar with concepts like indexing and performance optimization in SQL.
• Gain hands-on experience with SQL to retrieve, manipulate, and analyze data from databases.

Topics Covered

• The Module 3- SQL and Data Retrieval, which introduces basic concepts in SQL, an important relational database to be used by the data analyst. In this module, one learns to write SQL queries, know how to fetch and filter data. It moves to more sophisticated techniques for the SQL query using joins and aggregation. It expands more on data cleaning and validation through SQL, also discusses indexing and performance optimization of a database through SQL. Download Curriculum to Know the topics clearly.

Learning Outcomes

• Understand the principles of data visualization and become proficient in using Tableau.
• Learn how to connect, prepare, and analyze data using Tableau.
• Master the creation of interactive dashboards and visualizations in Tableau.
• Understand best practices in dashboard design and gain expertise in advanced data analysis techniques using Tableau.

Topics Covered

• The Module 4 - Data Visualization with Tableau introduces Tableau as the leading data visualization tool. It explains connecting and preparing data for use in Tableau and This module exposes the learner to interactive visualizations and dashboards. It depends More than what is viewed through the interface of Tableau, techniques on examining data. Thirdly, in the module comes the aspects regarding principles of effective design in developing a dashboard or the best presentation of data. Download Curriculum to be covered Learning those well.

Learning Outcomes

• Become familiar with the concept of business intelligence and master the use of Power BI for data cleansing, transformation, and analysis.
• Learn to create interactive visualizations and reports in Power BI.
• Understand the application of advanced analytics and machine learning in Power BI.
• Gain a deep understanding of the role of Power BI in data-driven decision-making and how it can be used for sales and marketing analytics.

Topics Covered

• The module 5 - Data Analysis with Power BI begins by introducing Power BI and its usage in business intelligence. The module teaches data cleansing and transformation skills within Power BI. Following data cleansing and transformation techniques, there are trainings in data modeling and DAX functions. Interactive visualization and reporting abilities within the tool are where it finally concludes. Advanced analytics and machine learning within Power BI is also a part of the discussions. This chapter places emphasis on the use of Power BI for business analysis, key metrics and KPIs, and also for data-driven decision-making. The chapter proceeds with further elaborate discussions on sales and marketing analytics through Power BI. Download Curriculum to Know the topics clearly.

Learning Outcomes

• Gain a comprehensive understanding of Python as a tool for data analysis.
• Learn to manipulate and analyze data using pandas, a popular Python library.
• Develop skills in exploratory data analysis and data visualization using Python libraries like Matplotlib and Seaborn.
• Master the concepts and techniques of statistical analysis and hypothesis testing using Python.

Topics Covered

• The Module 6 - Data Analysis with Python Introduces Python as an all-purpose language for data analysis. It has an important constituent called Exploratory Data Analysis (EDA) done using Python. It encompasses data visualization using Matplotlib and Seaborn, two very important libraries in Python. Lastly, it concludes by discussing in detail the statistical analysis and hypothesis testing using Python. That is what every data analyst should know. Download Curriculum to Know the topics clearly.

Learning Outcomes

• Apply the skills and knowledge acquired from the course in a practical work setting.
• Gain experience working on real data analytics projects.
• Develop professional skills such as teamwork, communication, and problem-solving.
• Receive feedback on performance and areas of improvement.
• Understand the challenges and dynamics of working in a data analytics role.

Topics Covered

• The final module allows students to be subjected to a simulated one-month internship of everything learned throughout their training. They will gain practical experience and receive feedback on their work, which is vital in transitioning from classroom learning to real-world application. This hands-on experience will help them understand and navigate the challenges of working as a data analyst.