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Skillfloor offers a comprehensive data analysis course designed to equip individuals with the necessary skills to excel in the field of data analytics. This course covers a wide range of topics essential for aspiring data analysts, providing in-depth insights into data collection, interpretation, and visualization techniques. With a focus on practical applications, students delve into statistical analysis, data manipulation, and predictive modelling, gaining hands-on experience through real-world projects. Whether you're a beginner looking to kickstart your career or a seasoned professional seeking to enhance your skills, Skillfloor's data analytics course offers valuable insights and practical knowledge to succeed in this field. 

Skillfloor's course for data analysts is meticulously crafted to meet the changing demands of the industry, offering a blend of theoretical knowledge and practical skills essential for success in the field. Through a structured curriculum, students explore advanced data analysis techniques, mastering tools and methodologies used to extract meaningful insights from complex datasets. From data cleansing and transformation to advanced analytics and machine learning algorithms, this course covers all aspects crucial for excelling in a data-driven environment. Whether you're aiming to advance your career or transition into a data analytics role, Skillfloor's course for data analysts provides the necessary foundation and expertise to thrive in this active field. 




Skill Level



1-month Unpaid

Live Project




Live Training


Career Assistance


Expiry Period

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Course Highlights

  • Introduction to Data Analysis: Learners start with the basics, understanding what data analysis entails and its importance in today’s data-driven world.

  • Data Types and Structures: The course covers different types of data (numerical, categorical) and how they are organized (e.g., in databases, and spreadsheets).

  • Excel for Analysis: An in-depth look at using Excel, focusing on formulas, functions, and pivot tables essential for analyzing data.

  • Introduction to Statistical Concepts: This includes understanding measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation) which are foundational for data analysis.

  • Data Cleaning Techniques: Learners are taught how to identify and correct errors in data, handle missing values, and ensure data quality.

  • Basic Data Visualization: The course highlights how to use charts, graphs, and other visualization tools to represent data findings effectively.

  • Introduction to SQL for Data Analysis: An overview of how to use SQL (Structured Query Language) to retrieve and manipulate data stored in databases.

  • Using Python for Data Analysis: This section introduces Python programming for data analysis, including libraries like Pandas and NumPy.

  • Data Interpretation and Decision Making: Focuses on how to interpret analysis results and make informed decisions based on data.

  • Project and Case Studies: The course culminates with practical projects and case studies where learners apply what they have learned to real-world data analysis scenarios.



This certificate, the Certified Data Analysis Associate, shows that someone has successfully finished a program to become really good at looking at data. They've learned important skills like how to analyze data with numbers, make it into pictures, and understand what it all means. They've used common tools and methods that professionals in the field use. They also know how to clean up data, change it if needed, and test their ideas about it. Having this certificate means that a person is good at using data to help make decisions. It's valuable for companies who want someone who can use data to make smart choices. If you have this certificate, it shows you're skilled at working with data and can stand out when it comes to using it to make decisions. It's especially good for people just starting in this field or for those who want to get better at using data.

Skillfloor-Certificate Skillfloor-Certificate

Internship Certificate


Completing this Analytics Course certifies your proficiency in data analysis, statistical methods, and essential analytics tools. This certification shows you can transform raw data into actionable insights, improving decision-making in various business contexts. It indicates your understanding of data visualization, predictive modelling, and data-driven strategy development, providing you with the skills to excel in analytics. This credential reflects your dedication to continuous learning and commitment to leveraging data for strategic advantage.

Tools Covered

Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudiotools_covered Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudio

Top 10 reasons

  1. Foundational Skills: You will be put on the right track to a successful career in data analysis with our Certified Data Analysis Associate course, which offers the fundamental information and practical skills required for aspiring data analysts.

  2. Career Possibilities: Obtain a well-respected credential that will increase your marketability and lead to a variety of job options in data analysis positions within sectors.

  3. Data Interpretation: Develop your ability to properly interpret and analyze data, turning unprocessed information into insights that can be used to make well-informed decisions.

  4. Statistical Analysis: Gain a thorough understanding of the basic statistical ideas and methods used in data analysis so that you can recognize patterns in the data and draw insightful conclusions.

  5. Gaining proficiency: data visualization tools and techniques will enable you to produce interesting and educational visualizations that effectively convey insights.

  6. Learning: the best practices and guiding principles of data management to maintain the accuracy and dependability of your data as you do research.

  7. Problem-Solving: Test your problem-solving abilities by taking on practical data analysis tasks and creating creative solutions to meet business objectives.

  8. Communication Skills: Develop your ability to persuade stakeholders of analytical results and recommendations, facilitating well-informed decision-making and promoting corporate objectives.

  9. Cooperation: Work together with colleagues on data analysis projects, encouraging cooperation and utilising group knowledge to meet project goals.

  10. Continuous progress: To be competitive in the data analysis profession, adopt an attitude of constant learning and progress. be up to date on industry trends and advancements.




  • Understanding the role of data analysis in business decision-making

  • Overview of basic data analysis concepts and terminology

  • Introduction to common data analysis tools and software

  • Techniques for collecting and organizing data

  • Data cleaning and preprocessing

  • Exploratory data analysis (EDA) techniques

  • Measures of central tendency and dispersion

  • Frequency distributions and histograms

  • Probability distributions


  • Hypothesis testing

  • Confidence intervals

  • Regression analysis

  • Principles of effective data visualization

  • Tools and techniques for creating visualizations

  • Interpreting and communicating insights from visualizations


  • Overview of machine learning concepts and algorithms

  • Supervised vs. unsupervised learning

  • Model evaluation and selection


  • Introduction to predictive modeling

  • Decision trees and random forests

  • Logistic regression and classification


  • Understanding time series data

  • Techniques for analyzing and forecasting time series data

  • Seasonality and trend analysis


  • Challenges and opportunities of big data

  • Introduction to distributed computing frameworks (e.g., Hadoop, Spark)

  • Techniques for processing and analyzing large datasets


  • Ethical considerations in data analysis

  • Legal and regulatory frameworks for data privacy

  • Best practices for ensuring data security and privacy



A certified data analysis associate is someone who has earned a recognized certification in data analysis, showing they have the skills and knowledge to work in the field.

To become certified, you typically need to complete specific training courses and pass an exam administered by a certifying body.

Skills like problem-solving, critical thinking, attention to detail, and proficiency in tools like Excel, Python, or R are essential for data analysis.

You can pursue roles like data analyst, business analyst, data scientist, or market analyst in various industries.

obtaining certification can provide you with valuable skills and credentials that can enhance your career prospects and earning potential.

The exam usually tests your knowledge of data analysis techniques, tools, and best practices.


Many certification programs offer online courses and exams, making it convenient to study and test from anywhere.

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