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JUMPSTART YOUR

Online Data Science Course

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Price

₹6,000.00

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Overview:

This 3-week course is designed to introduce learners to the core concepts and techniques of data science. Through interactive lessons and practical projects, participants will gain hands-on experience with statistical analysis, data manipulation, visualization, and predictive modeling using Python.

What You’ll Learn

  • Basics of statistical analysis and how it applies to data science.
  • Data manipulation and cleaning techniques using Python libraries.
  • Fundamental principles of machine learning and predictive modeling.
  • Creating effective data visualizations to communicate findings.
  • Best practices for data science, including data ethics and data privacy.

Course Content

Module 13: Advanced Machine Learning
Lesson 1: Boosting and Bagging 2 Topics
Lesson Content
0% Complete 0/2 Steps
Lesson 2: Gradient Boosting and Other Techniques 3 Topics
Module 14: Natural Language Processing
Lesson 1: NLP 5 Topics
Module 15: Time Series Analysis
Lesson 1: Time Series Basics 2 Topics
Lesson 2: Forecasting Techniques 3 Topics
Lesson Content
0% Complete 0/3 Steps
Module 16: Big Data and Cloud Computing
Lesson 1: Big Data Concepts 3 Topics
Lesson 2: Cloud Computing for Data Science 1 Topic
Lesson Content
0% Complete 0/1 Steps
2 of 2

FAQs

1. What is Data Science in basic terms, and why does it matter?

Data Science is the field of extracting meaningful insights from structured and unstructured data using statistical techniques, algorithms, and machine learning. It’s vital for making data-driven decisions in industries like healthcare, finance, retail, and tech.

2. Who should take the Data Science Fundamentals course?

This data scientist masters program online is perfect for beginners interested in transitioning to data science roles, working professionals looking to upskill, and students aspiring to build a career in analytics, AI, or business intelligence.

3. What will I learn in the Data Science Fundamentals course?

You’ll learn:
Basics of Python and its libraries for data science.
Data cleaning, preprocessing, and visualization techniques.
Core statistical concepts like regression and probability.
An overview of machine learning algorithms and their uses.

4. How long does it take to complete the Data Science Fundamentals course?

The course is structured to be completed in 2 to 3 weeks, with a commitment of 1 hour per day. This flexible schedule makes it manageable for busy learners.

5. Are there prerequisites for enrolling in this course?

No prior experience is required. Basic computer skills and familiarity with spreadsheets or data handling will be helpful but are not mandatory.

6. Will I work on real-world data during the course?

Yes, the online data science course includes hands-on projects using real-world datasets. You’ll perform tasks such as cleaning messy data, visualizing trends, and building simple predictive models.

7. What tools and libraries will I learn in this course?

You’ll gain practical experience with:
Python libraries: Pandas, NumPy, Matplotlib, and Seaborn.
Jupyter Notebook for coding and visualization.
Introductory exposure to machine learning with scikit-learn.

8. What career paths can I explore after completing this course?

You can pursue entry-level roles such as Data Analyst, Junior Data Scientist, or Business Intelligence Analyst. This course lays the foundation for advanced learning in machine learning and AI.

9. Is a certification provided for this course?

Yes, you’ll receive a Data Science Fundamentals Certificate upon completion. This data science online course with certificate demonstrates your skills and is a valuable addition to your resume.

10. How does this course differ from advanced data science courses?

While advanced courses focus on deep machine learning, big data, and AI, this course covers the foundational skills like data analysis, visualization, and basic statistical modeling, making it an essential starting point for beginners.

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