Course Highlights
Advanced Data Analytics and Visualization is a comprehensive 200+ hour program designed to transform beginners into industry-ready data professionals capable of working across the complete data analytics pipeline, from data collection and cleaning to visualization and storytelling.
- To make you learn data analytics comprehensively, we have structured the course into five progressive modules - each focusing on one essential pillar of analytics:
- Python Programming for Analytics – Learn programming logic, functions, OOPs, and file handling to build a strong coding foundation for data analysis
- Exploratory Data Analysis (EDA) using Python – Dive deep into data with NumPy, Pandas, Matplotlib, and Seaborn; perform end-to-end analysis and real-world case studies, including web scraping for data collection
- Advanced Statistics for Analytics – Understand data distributions, sampling, and hypothesis testing with real-time statistical applications using Python’s SciPy library
- MySQL for Data Analytics – Master database querying, joins, aggregations, and analytical data extraction to manage large-scale structured datasets
- Power BI and Excel for Data Visualization – Build interactive dashboards and business reports, culminating in a full-scale Sales Analytics Dashboard project that connects insights to business outcome
- The program emphasizes hands-on practice through projects, exercises, and case studies that simulate real business analytics environments.
- Learners gain end-to-end exposure to analytical thinking, statistical reasoning, SQL querying, and visualization storytelling using industry-standard tools - Python, MySQL, Power BI, and Excel.
- The course is aligned with NASSCOM FutureSkills Prime guidelines, ensuring that learners acquire competencies relevant to emerging roles such as Data Analyst, Business Analyst, MIS Executive, and Junior Data Scientist.
- Designed and delivered by industry experts, this program combines conceptual clarity, tool proficiency, and business application to make you job-ready in the field of Data Analytics and Visualization.
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Skill Type
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Course Duration
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Domain
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GOI Incentive applicable
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Nasscom Assessment
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Placement Assistance
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Certificate Earned
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NOS Details
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Mode of Delivery
Course Details
What will you learn in the Advanced Data Analytics Course?
By the end of this course, students will be able to:
- Apply Python Programming fundamentals to data manipulation and analytics tasks
- Perform end-to-end Exploratory Data Analysis (EDA) using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn
- Understand and implement advanced statistical techniques including probability distributions, hypothesis testing, confidence interval estimation, and feature engineering
- Extract, manipulate, and analyze structured data using MySQL for real-world business scenarios
- Design and develop interactive dashboards and visualizations in Power BI and Excel to communicate actionable insights
- Integrate data from multiple sources to solve complex analytical problems.
- Execute hands-on analytics projects to derive business recommendations and support data-driven decision-making
Why should you take the Advanced Data Analytics Course?
- Industry-recognized Curriculum: Designed in alignment with NASSCOM FutureSkills Prime standards and industry expectations
- Comprehensive Learning Path: Covers the entire analytics pipeline, from Python programming to dashboard storytelling
- Hands-on Practice: Work on real-world projects like Sales Analytics Dashboard and Web Scraping for Data Collection & Cleaning
- Career-driven Outcome: Prepare for roles such as Data Analyst, Business Analyst, MIS Executive, or Junior Data Scientist
- Tool Mastery: Gain practical experience in Python, Pandas, MySQL, Excel, and Power BI
- Expert-led Training: Learn directly from industry practitioners with years of data analytics and visualization expertise
- Portfolio Building: Create data-driven projects to showcase to employers and strengthen your resume
- Job Readiness: Learn how to convert data into insights, and insights into strategic business decisions
Who should take the Advanced Data Analytics Course?
- Fresh graduates or final-year students looking to start a career in Data Analytics
- BBA, B.Com, B.Sc, or Engineering students seeking data-driven career roles
- Professionals from non-technical backgrounds who want to transition into analytics
- CSE or IT graduates aiming to strengthen their applied analytics and visualization skills
- Business professionals, entrepreneurs, and working executives who want to make data-informed decisions
- Anyone who is curious about how data analytics drives modern businesses
Curriculum
The Advanced Data Analytics and Visualization program is a comprehensive 200+ hour hands-on training designed to equip learners with in-demand analytical, statistical, and visualization skills.
To make learning structured and progressive, the course is divided into five modules, each focusing on key aspects of Data Analytics:
Module 1: Python Programming for Analytics
Get started with Python, the language of data:
- Fundamentals, data types, operators, and control flow
- Functions and OOP concepts
- File handling and exceptions
- Writing reusable and efficient code for data manipulation
Module 2: Exploratory Data Analysis (EDA) using Python
Understand your data through exploration and visualization. Topics include:
- Descriptive statistics and probability distributions
- Data manipulation using NumPy and Pandas
- Advanced data visualization with Matplotlib and Seaborn
- Real-world case studies and EDA projects
- Web scraping and data collection exercises
Module 3: Advanced Statistics for Analytics
Master the core of data interpretation with:
- Discrete and continuous data distributions
- Normal distribution and data transformations
- Sampling, CLT, and confidence interval estimation
- Hypothesis testing using SciPy
- End-to-end analytical project applications
Module 4: MySQL for Data Analytics
Become fluent in data querying and relational database operations:
- SQL syntax, joins, and subqueries
- Aggregations and data summarization
- Data extraction and integration with Python
- Analytical use cases using real datasets
Module 5: Power BI and Excel for Data Visualization
Convert data into actionable insights and interactive dashboards:
- Data cleaning and modeling in Power BI
- Creating visuals, KPIs, and reports
- DAX functions and measures
- Excel for analytics and reporting
- End-to-end Sales Analytics Dashboard project
By the end of this course, you will confidently handle data from raw collection to meaningful visualization, making you job-ready for analytics roles.
Tools you will learn in the Advanced Data Analytics Course
In this course, you will gain expertise in both analytical thinking and tool-based execution.
Key Skills:
- Data Cleaning & Preparation
- Data Wrangling & Transformation
- Exploratory Data Analysis (EDA)
- Statistical Inference & Hypothesis Testing
- Feature Engineering
- SQL Querying for Business Analytics
- Dashboarding & Storytelling with Data
Tools Covered:
- Python (NumPy, Pandas, Matplotlib, Seaborn, SciPy)
- MySQL
- Power BI
- Microsoft Excel
- Jupyter Notebook/Visual Studio Code
- Web Scraping Tools (BeautifulSoup/Requests)