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Graphic Design

Data Analytics

This course provides a comprehensive introduction to the field of data analytics. It is designed for individuals who are interested in learning about the tools, techniques, and methodologies used to analyze large datasets and extract meaningful insights. By the end of the course, students will be equipped with the knowledge and skills necessary to apply data analytics in real-world scenarios, making them valuable assets in any industry that relies on data-driven decision making. Whether you’re a beginner looking to start a career in data analytics or a professional seeking to enhance your skills, this course offers a solid foundation in this rapidly growing field.

Course Features

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Total 40 Hours

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Income and Freelancing Guidelines

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Tools, templates and book suggestions

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Online and Offline Support

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Recorded video

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Assessment and Certificate

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Job Placement Support

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Course duration is 3 months

৳ 10000 ৳ 20000

For details about the course

Call Now (0179-944-6655)

Course Features

Data Analytics course is professionally designed with detailed discussions on web design and development, on-hand practice and income guidelines.

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Total 40 Hours

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Income and Freelancing Guidelines

icons

Tools, templates and book suggestions

icons

Online and Offline Support

icons

Recorded video

icons

Assessment and Certificate

icons

Job Placement Support

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Course duration is 3 months

Course Modules

  • What is data analytics?
  • Applications of data analytics in different fields
  • The data analytics lifecycle (data acquisition, cleaning, transformation, analysis, visualization)


  • Different types of data (structured, unstructured, semi-structured)
  • Common data sources (databases, web scraping, social media)
  • Introduction to data quality concepts


  • Basics of relational databases
  • SQL syntax and queries
  • Data retrieval using SELECT, WHERE, and JOIN statements
  • Aggregations and grouping data
  • Subqueries and nested queries
  • Data manipulation using INSERT, UPDATE, and DELETE


  • Python programming basics
  • Setting up the environment: Anaconda and Jupyter Notebooks
  • Data structures in Python (lists, dictionaries, tuples)
  • Introduction to Pandas library


  • Data cleaning techniques (handling missing values, outliers, inconsistencies)
  • SQL/Python for data manipulation
  • Working with data in spreadsheets
  • Combining data from multiple sources
  • Real-world data analysis project using Python


  • Descriptive statistics (measures of central tendency, dispersion)
  • Inferential statistics (hypothesis testing, correlation analysis)
  • Introduction to probability concepts


  • Principles of effective data visualization
  • Creating different chart types (bar charts, line charts, scatter plots)
  • Advanced visualizations with Seaborn
  • Overview of Power BI interface and functionalities
  • Data transformation using Power Query
  • Basic DAX functions and calculations (Data Analysis Expressions)
  • Building interactive dashboards publishing and sharing reports


  • Effective data storytelling techniques
  • Presenting data insights to different audiences
  • Ethical considerations in data collection and analysis


  • ETL, Data Orchestration, Big Data, Data Science, ML/AI, and data management ecosystem 

  • Students will participate in weekly labs where they apply the concepts learned in lectures to real-world datasets.
  • Culminating project: Students will work on a course-long project where they choose a dataset, analyze it using the learned techniques, and create visualizations to communicate their findings.


  • Weekly quizzes and assignments based on lectures and labs
  • Final project presentation and report


What you will learn

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Python

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Database Table

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Spreadsheet software

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SQL database management system

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Data visualization tool

Details about the course

This course provides a comprehensive introduction to the field of data analytics. It is designed for individuals who are interested in learning about the tools, techniques, and methodologies used to analyze large datasets and extract meaningful insights.

Throughout the course, students will learn how to:

Understand the fundamentals of data analytics, including its importance and applications in various industries.

Gain proficiency in data collection, cleaning, and preprocessing techniques to prepare data for analysis.

Master the use of statistical methods and machine learning algorithms to analyze and interpret complex datasets.

Develop skills in using data visualization tools to effectively communicate analytical results.

Learn to use popular data analytics software and tools, such as Python, R, SQL, and Tableau.

Understand the ethical considerations in data analytics, including data privacy and security.

By the end of the course, students will be equipped with the knowledge and skills necessary to apply data analytics in real-world scenarios, making them valuable assets in any industry that relies on data-driven decision making. Whether you’re a beginner looking to start a career in data analytics or a professional seeking to enhance your skills, this course offers a solid foundation in this rapidly growing field.

Course Certificate

Get Course Completion and Assessment Certificate at the end of the course

On successful completion of the course you will receive a certificate which will enable you to-

  • Can add to your CV
  • You can share directly on your LinkedIn profile
  • You can share on Facebook with one click

Frequently Asked Questions

এটা তো আসলে ব্যক্তিবিশেষে আলাদা – কারো কম সময় লাগবে, কারো বেশি সময় লাগবে! তবে আশা করা যায়ঃ প্রতি সপ্তাহে গড়ে ১০-১৫ ঘণ্টা করে সময় দিলে আপনি পুরো সিলেবাস শিখে ফেলতে পারবেন।

হ্যাঁ, অবশ্যই। কোর্স শেষে সার্টিফিকেট তো থাকছেই। তবে এজন্য ৬ মাসের ভেতর কোর্স শেষ করতে হবে। কারণ প্রজেক্ট রিভিউর মতো ব্যাপারগুলো এ ৬ মাস পর থাকবে না।

আমাদের প্রতিটা কোর্সের আপকামিং সিডিউল দেওয়া আছে। আপকামিং সিডিউল দেখে আপনি ভর্তি কনফার্ম করতে পারেন অথবা আপনার ফ্লেক্সিবিলিটি অনুযায়ী কোর্স করতে পারবেন।

নির্দিষ্ট কোনো ডিগ্রি রিকোয়্যারমেন্ট নেই। তবে কমপক্ষে এইচএসসি বা সমমানের যোগ্যতা থাকা উচিত। এছাড়া, STEM (Science, Technology, Engineering, Mathematics) ব্যাকগ্রাউন্ডের শিক্ষার্থীদের জন্য এ কোর্স তুলনামূলকভাবে সহজ হবে। অবশ্য নন-টেকনিক্যাল (যেমন, কমার্স কিংবা আর্টস) ব্যাকগ্রাউন্ডের মানুষরাও এ কোর্স করতে পারবে। পাশাপাশি কয়েকটি বেসিক বিষয় জানতে হবে। যেমন, Basic Algebra সম্পর্কে ভাল ধারণা থাকা। আবার কম্পিউটার চালানো এবং ইন্টারনেট ব্রাউজার ব্যবহারে কমফোর্টেবল হতে হবে। এছাড়া, গুগলে সার্চ করে কোনো টপিক ঘেঁটে দেখার মতো অভ্যাস থাকা উচিত।

Any more query?

Call For Any Information Regarding The Course +880179-944-6655 (09 AM to 09 PM)

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