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Data Science Fundamentals Part 1: Unit 1
This course demystifies core data science concepts and techniques through engaging Python lessons and real datasets. You’ll gain practical experience working with the Python ecosystem, including pandas, NumPy, scikit-learn, and more, as you analyze authentic data and build meaningful applications from scratch. From setting up your programming environment to building your first recommendation engine, each lesson emphasizes intuition, best practices, and the computational skills needed to tackle “undomesticated” data problems. No advanced math or statistics background required—just a willingness to learn and a basic familiarity with programming. By the end of the course, you’ll have built real projects, mastered essential data science workflows, and developed the confidence to apply machine learning algorithms to real-world challenges.
Duration
7 Months
Institution
Pearson
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Pearson.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$275
Total Est. Investment
$275
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Data Science Fundamentals Part 1: Unit 1 program at Pearson are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.