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CCDSCore Concepts in Data Science
التقييم:
الإنجليزي
متوسط
لا توجد جلسات متاحة في هذه اللحظة.
تواصل مع مستشار التدريب لدينا لمعرفة المزيد عن الجلسات المتاحة التالية.
لتحميل الكتيب
نبذة عن الدورة التدريبية
المخرجات الرئيسية
Harvard University
This program is from Harvard’s Office of the Vice Provost for Advances in Learning (VPAL), in association with HarvardX. It is offered in collaboration with GetSmarter, an edX partner.Gain a holistic perspective on cybersecurity risk and mitigation, and get recognised for your knowledge with a premier certificate from Harvard’s VPAL.
محتوى الدورة التدريبية
DAY 1 Introduction to Data Science and R Basics
→ Module 1: Welcome and Program Overview
→ Module 2: Introduction to Data Science
→ Module 3: Understanding Data Types in R
→ Module 4: Basic R Programming Exercises
→Module 5: Data Frames and Data
Manipulation in R
→ Module 6: Programming Concepts:
Functions, Loops, and Conditionals
→ Module 7: Data Handling Practical Session
→ Module 8: Q&A and Wrap-Up
DAY 2 Data Visualization with R
→ Module 1: Principles of Data Visualization
→ Module 2: Introduction to ggplot2 in R
→ Module 3: Creating Basic Plots (Histograms,
Scatter Plots)
→ Module 4: Advanced Plotting Techniques
→ Module 5: Customizing Plots and Themes
in ggplot2
→ Module 6: Hands-on Exercise: Creating
Visualizations
→ Module 7: Q&A and Wrap-Up .
DAY 3 Probability and Its Applications
→ Module 1: Fundamental Concepts in
Probability
→ Module 2: Random Variables and
Probability Distributions
→ Module 3: Applying Probability in Data
Science
Module 4: Statistical Inference and
Probability
→ Module 5: Case Study: Real-World
Applications
→ Module 6: Hands-on Exercise: Probability
Problems in R
→ Module 7: Q&A and Wrap-Up
DAY 4 Inference and Modeling
→ Module 1: Introduction to Statistical Inference
→ Module 2: Building Statistical Models
→ Module 3: Hypothesis Testing
→ Module 4: Regression Analysis
→ Module 5: Practical Session: Inference and
Modeling in R
→ Module 6: Model Evaluation Techniques
→ Module 7: Q&A and Wrap-Up.
DAY 5 Productivity Tools for Data Science
→ Module 1: Enhancing Productivity with
Tools
→ Module 2: Version Control with Git and
GitHub
→ Module 3: Using RStudio for Data Science
Projects
→ Module 4: Reproducible Research with
Markdown
→ Module 5: Hands-on Exercise: Productivity
Tools
→ Module 6: Final Project Overview and
Guidelines
→ Module 7: Q&A and Program Wrap-Up
على من يجب الحضور؟
This highly practical and interactive course has been specifically designed for
→Business and Data Analysts: Professionals
who need to analyze and report on data to
inform business decisions.
→Project Managers: Those who manage
projects and require data to plan and
report progress.
→Finance Professionals: Analysts and
managers who need to handle complex
financial data and forecasts.
→IT Professionals: Those who support
data systems and need to understand
data flows and reporting.
→Operations Managers: Managers needing to
optimize operations through data analysis.