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Fundamentals of Data Science

FREE


Instructor: upskillcampus



Language: English, Hindi

Course Description

Data is the driving force of the modern digital economy. Organizations across all industries rely on data-driven insights to make informed decisions and optimize performance. The Data Science Training Program is designed to equip learners with the skills and tools required to collect, analyze, visualize, and interpret data effectively. This program provides a strong foundation in statistics, programming, machine learning, and data visualization, helping participants transform raw data into actionable intelligence. Through real-world projects and hands-on learning, students will gain the expertise needed to solve complex business problems and pursue a career in one of the most in-demand fields today. This course offers a complete, practical approach to data science, covering all stages of the data lifecycle. Learners begin with Python for data analysis, followed by statistical methods, data cleaning, and visualization using tools such as NumPy, Pandas, Matplotlib, and Power BI/Tableau.


What You will learn in this Course:

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

  • Understand the fundamentals of data science, analytics, and data-driven decision-making.
  • Perform data cleaning, transformation, and visualization using Python and visualization tools.
  • Apply statistical and machine learning techniques for predictive analytics.
  • Build, evaluate, and optimize machine learning models.
  • Present insights through dashboards and visual storytelling.
  • Handle real-world datasets and build end-to-end data science projects.


Syllabus

What do we offer

Lifetime Access

Get life long access to all the courses with unlimited learning.

Structured learning

Our curriculum is designed by experts to make sure you get the best learning experience.

Community & Networking

Interact and network with like-minded folks from various backgrounds in exclusive chat groups.

Learn with the best

Stuck on something? Discuss it with your peers and the instructors in the inbuilt chat groups.

Practice tests

With the quizzes and live tests practice what you learned, and track your class performance.

Get certified

Flaunt your skills with course certificates. You can showcase the certificates on LinkedIn with a click.

FAQs

Data Science offers strong and rapidly growing career opportunities because companies depend heavily on data for business decisions and automation.

Job Roles:

  • Data Analyst
  • Data Scientist
  • Machine Learning Engineer
  • Business Analyst
  • AI/ML Developer
  • Data Engineer
  • Research Analyst

Industries Hiring Data Science Professionals:

  • IT & Software
  • E-commerce, FinTech, EdTech, HealthTech
  • Banking & Insurance
  • AI/ML and Analytics companies
  • Consulting and Research firms

You can learn Data Science by following a structured and step-by-step learning approach.

1. Learn the Fundamentals:

  • Python programming
  • Statistics & probability basics
  • Data analysis and data cleaning
  • NumPy, Pandas, Matplotlib

2. Learn Core Data Science Skills:

  • Machine learning fundamentals
  • Supervised and unsupervised learning
  • Model evaluation and optimization
  • Data visualization tools

3. Build Real Projects:

  • Data analysis projects
  • Prediction and classification models
  • Recommendation systems
  • Machine learning-based mini projects
  • Strengthen Python, statistics, machine learning algorithms, and data analysis concepts.
  • Practice working with Pandas, NumPy, and visualization tools.
  • Understand supervised and unsupervised ML algorithms clearly.
  • Build at least 2–3 strong ML projects and understand end-to-end workflow.
  • Prepare SQL basics and common analytical queries.
  • Learn how to explain model performance and optimization techniques.
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