Data Analyst Course – Live Training
Isha presents an Extensive and highly interactive “Data Analyst” Course by our industry expert with 12 years of hands-on experience. Learn all the Data Analyst concepts with hands-on practical examples. The course syllabus is designed by considering the current job market trends and industry requirements.
About the Instructor:
| Abhishek has nearly 12 years of experience in various domains like life sciences, finance and accounting in solving business problems using Data Science, Business Analytics and Business intelligence. Mostly working with CTOs, Key IT decision-makers, and Professionals, He always focused on building capacity, knowledge and solutions in Data Science, Business Analytics and Business Intelligence. He has 4+ years of experience in training freshers and corporate employees. In his Knowledge sharing trained more than 300+ Students. He has given a lot of corporate trainings for different organizations on different courses like Python, Data Science and Power BI. |
Sample Videos:
“Data Analyst Course -Live Training Demo Video”:
“Data Analyst Course -Live Training Day 1 Video”
Live Sessions Price:
For LIVE sessions – Offer price after discount is 200 USD 199 150 USD Or USD20000 INR 17000 INR 11900 Rupees.
OR
Free Day 3 On:
Learners in India: 8th March @ 7:30 AM to 8:30 AM (IST)
Learners in the US: 7th March @ 9 PM to 10 PM (EST)
Learners in the UK: 8th March @ 2 AM – 3 AM (BST)
Class Schedule:
For Participants in India: Monday to Friday @ 7:30 AM – 8:30 AM (IST)
For Participants in the US: Sunday to Thursday 9 PM – 10 PM (EST)
For Participants in the UK: Monday to Friday 2 AM – 3 AM (BST)
What student’s have to say about Abhishake:
| Great Course with awesome exercises sufficient to call it hands-on. – Sahana
The course is good. The trainer explains everything in details thoroughly and carefully. – Siddharth I am impressed with this instructor. So far so great! – Amilcar It’s a good course, it was explained step by step for easy understanding. The quality of the videos is excellent in Full HD which helps see all the data on Excel. The Python course is good for beginners – Patrick It is going to be a good experience since I always asked someone else to perform my pivot tables, and I will be able to start doing it myself. – Gurpreet I am enjoying this course. a complete package for data analysts – Dikshita |
Who can enroll for this course?
This course is suitable for a diverse range of individuals interested in developing skills in data analysis, regardless of their prior experience or background. Potential candidates who may enroll include:
- Students or recent graduates seeking to enter the field of data analysis and enhance their employability.
- Professionals from various industries aiming to transition into roles involving data analysis or seeking to upskill.
- Data enthusiasts looking to expand their knowledge and proficiency in SQL, Python, and Power BI.
- Business professionals interested in leveraging data to drive decision-making within their organizations.
- Anyone interested in exploring the intersection of technology and data to extract insights and inform strategic decisions.
Overall, this course caters to individuals with a keen interest in data analysis and a desire to develop practical skills in SQL, Python, and Power BI, irrespective of their educational or professional background.
What will I Learn by end of this course?
By the end of this data analyst course, students will have gained comprehensive knowledge and practical skills in various aspects of data analysis using SQL, Python, and Power BI. Here’s what they will learn:
- Introduction to Data Analysis:
- Understand the definition and importance of data analysis in decision-making processes.
- Overview of SQL, Python, and Power BI in Data Analysis:
- Get a brief introduction to SQL, Python, and Power BI.
- Understand how each tool contributes to the data analysis process.
- SQL Fundamentals with PostgreSQL:
- Learn about databases and PostgreSQL.
- Gain proficiency in writing basic and advanced SQL queries.
- Understand data manipulation techniques such as aggregation, filtering, and joining.
- Explore advanced SQL concepts like subqueries, CTEs, and indexes.
- Python for Data Analysis with Pandas:
- Get introduced to Python programming language.
- Understand Pandas library and its components like Series, DataFrames, and Indexing.
- Learn data wrangling techniques, including handling missing data and data transformation.
- Explore exploratory data analysis (EDA) and data visualization using Pandas.
- Power BI Fundamentals:
- Understand the components of Power BI and its role in data analysis.
- Learn how to use Power BI Desktop for data visualization and modeling.
- Gain proficiency in importing data from various sources and performing data modeling using DAX.
- Learn to create basic and advanced visualizations, reports, and dashboards.
- Understand how to share and collaborate on reports using Power BI Service.
By the end of the course, students will be equipped with the necessary skills to perform data analysis tasks proficiently using SQL, Python, and Power BI. They will be able to extract insights from data, create meaningful visualizations, and communicate their findings effectively to support decision-making processes in various domains. Additionally, they will have access to additional resources for further learning and exploration in the field of data analysis.
Salient Features:
- Approximately 45 Hours of Live Training
- Every session gets recorded and lifetime access to these videos will be given.
- Course Completion Certificate
Course syllabus:
Module 1: Introduction to Data Analysis (2 hours)
- What is Data Analysis?
- Definition of data
- Importance of data analysis in decision-making
- Overview of SQL, Python, and Power BI in Data Analysis (2 hours)
- Brief introduction to SQL, Python, and Power
- Explanation of how each tool contributes to the data analysis
Module 2: SQL Fundamentals with PostgreSQL (10 hours)
- Introduction to Databases and PostgreSQL (1.5 hours)
- Explanation of databases and PostgreSQL.
- Installing and setting up PostgreSQL.
- SQL Basics: Syntax and Querying Data (2 hours)
- Understanding SQL Syntax
- Writing basic SQL queries to retrieve data from databases.
- Working with Data: Aggregation, Filtering, and Joins (2 hours)
- Aggregating data using GROUP By
- Filtering data using WHERE clause
- Performing joins to combine data from multiple tables.
- Advanced SQL Concepts: Subqueries, CTEs, and Indexes (1.5 hours)
- Writing subqueries to perform complex queries
- Utilizing Common Table Expressions (CTEs).
- Introduction to indexes for optimizing query performance.
- Data Manipulation: Inserting, Updating, and Deleting Data (2 hours)
- Inserting new data into tables
- Updating existing data
- Deleting data from tables
Module 3: Python for Data Analysis with Pandas (15 hours)
- Introduction to Python for Data Analysis (1.5 hours)
- Introduction to Python programming language.
- Overview of Python’s role in data analysis.
- Introduction to Pandas: Series, DataFrames, and Indexing (2 hours)
- Explanation of Pandas Library.
- Understanding Series, DataFrames, and Indexing.
- Data Wrangling with Pandas: Cleaning and Transformation (3 hours)
- Handling Missing Data
- Data cleaning techniques
- Transforming data using Pandas.
- Exploratory Data Analysis (EDA) with Pandas (2.5 hours)
- Performing descriptive staƟsƟcs.
- Exploring data distribuƟons.
- Visualizing data with Pandas.
- Advanced-Data Analysis Techniques with Pandas (2.5 hours)
- Advanced indexing and selecƟon.
- Reshaping and pivoting data.
- Working with text data.
- Data Visualization with Pandas (3.5 hours)
- Basic visualization using built-in Pandas plotting capabiliƟes.
- Customizing plots for better insights.
Module 4: Power BI Fundamentals (17 hours)
- Introduction to Power BI: Overview and Components (2 hours)
- Overview of Power BI tool.
- Understanding Power BI Desktop, Service, and Mobile
- Getting Started with Power BI Desktop (2 hours)
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- InstallaƟon and configuraƟon of Power BI Desktop.
- Exploring the user interface and navigation.
- Data Sources and Data Import (3 hours)
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- Connecting to various data sources
- Importing data into Power BI
- Power BI Data Modeling and DAX (6 hours)
- Power BI Data Modeling Fundamentals (1.5 hours)
- Understanding data modeling concepts in Power BI
- Importance of data modeling for creating meaningful visualizaƟons.
- Overview of relationships, tables, and columns in Power BI data models.
- Introduction to DAX (2 hours)
- Understanding the basics of Data Analysis Expressions (DAX).
- Syntax and structure of DAX formulas.
- Common DAX functions for calculations and aggregations.
- Advanced DAX Functions and Techniques (2.5 hours)
- Exploring advanced DAX functions for complex calculaƟons.
- Utilizing DAX iterators for iterating over table rows.
- Implementing time intelligence functions for date-based analysis.
- Power BI Data Modeling Fundamentals (1.5 hours)
- Data Visualization with Power BI (4 hours)
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- Creating basic visualizaƟons.
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- Using interactive features like slicers and filters.
- Customizing visualizations for better insights
- Advanced Visualization Techniques (2 hours)
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- Utilizing advanced visualizations.
- Working with custom visuals and third-party integrations
- Creating Reports and Dashboards (2 hours)
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- Building reports with multiple visualizations.
- Designing interactive dashboards for data exploration.
- Sharing and Collaboration with Power BI Service (1 hour)
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- Publishing reports to Power BI Services
- Setting up workspaces and managing collaboration.
- Accessing reports using Power BI mobile app.
Additional Resources (1 hour)
- Online tutorials, documentation, for SQL, Python, and Power BI.