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Last updated:

August 12, 2023


Unlimited Duration

Original price was: $49.00.Current price is: $15.00.

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration


This 25-day mastery course on Introduction to Data Science is designed for postgraduate students and professionals who want to gain comprehensive knowledge and hands-on experience in the field of data science.

The course covers a wide range of topics, including data collection, preprocessing, exploratory data analysis, machine learning, data visualization, big data, natural language processing, and real-world data science projects. Participants will learn how to use various data science tools and technologies to extract valuable insights from data and solve complex problems in diverse industries.

Learning Outcome: 

By the end of this course, participants will be able to:

  • Understand the data science lifecycle and its application in various industries.
  • Collect, preprocess, and analyze data to derive meaningful insights.
  • Apply machine learning algorithms for predictive modeling and decision-making.
  • Visualize and communicate data insights effectively to stakeholders.
  • Process and analyze big data using distributed computing frameworks.
  • Implement natural language processing techniques for text mining and sentiment analysis.
  • Work on real-world data science projects and collaborate with teams.
  • Apply best practices and ethical considerations in data science.

Suitable for:

Postgraduate students and professionals from diverse academic backgrounds.

Aspiring data scientists and analysts looking to enter the field of data science.

Professionals seeking to upskill and enhance their knowledge in data science.

Business analysts and data professionals who want to understand the data science workflow and techniques.

Course Curriculum

    • Course Overview and Objectives Unlimited
    • Understanding the Data Science Lifecycle Unlimited
    • Role of Data Scientists in Various Industries Unlimited
    • Introduction to Data Science Tools and Technologies Unlimited
    • Chapter 1- Test 00:10:00
    • Sources of Data and Data Types Unlimited
    • Data Collection Methods Unlimited
    • Data Cleaning and Data Quality Assessment Unlimited
    • Data Transformation and Feature Engineering Unlimited
    • Chapter 2 – Test 00:20:00
    • Understanding the Importance of EDA Unlimited
    • Data Visualization Techniques Unlimited
    • Statistical Measures for EDA Unlimited
    • Identifying Patterns and Trends in Data Unlimited
    • Data Cleaning and Preprocessing for EDA Unlimited
    • EDA with Real-world Datasets Unlimited
    • Chapter 3 – Test 00:20:00
    • Overview of Machine Learning Concepts Unlimited
    • Supervised, Unsupervised, and Reinforcement Learning Unlimited
    • Model Training and Evaluation Unlimited
    • Model Selection and Hyperparameter Tuning Unlimited
    • Chapter 4 – Test 00:10:00
    • Principles of Data Visualization Unlimited
    • Creating Effective Data Visualizations Unlimited
    • Communicating Data Insights to Stakeholders Unlimited
    • Using Dashboards for Data Presentation Unlimited
    • Chapter 5 – Test 00:10:00
    • Introduction to Big Data and its Challenges Unlimited
    • Distributed Computing Frameworks (e.g., Hadoop, Spark) Unlimited
    • Processing and Analyzing Big Data Sets Unlimited
    • Scalable Machine Learning on Big Data Unlimited
    • Chapter 6 – Test 00:25:00
    • Basics of Natural Language Processing (NLP) Unlimited
    • Text Preprocessing and Feature Extraction Unlimited
    • Sentiment Analysis and Text Classification Unlimited
    • Applications of NLP in Industry Unlimited
    • Chapter 7 – Test 00:20:00
    • Working on a Data Science Project from Start to Finish Unlimited
    • Applying Data Science Techniques to Real-world Problems Unlimited
    • Collaboration and Communication in Data Science Projects Unlimited
    • Best Practices and Ethical Considerations in Data Science Unlimited
    • Chapter 8 – Test 00:20:00

About the instructor

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