Description
Introduction to Data Science
Course Overview:
This course introduces beginners to the data science lifecycle using Python. Learn how to clean, analyze, and visualize data.
What You’ll Learn:
– Data analysis with Pandas and NumPy
– Data visualization with Matplotlib
– EDA and statistics
– Simple machine learning with Scikit-learn
Course Structure:
10 Modules from Python basics to a real-world capstone project.
Duration: ~40 hours
Final Statement:
Complete this course with the ability to extract insights from data and a strong foundation for machine learning or data analysis careers.
Buhari –
“This ‘Introduction to Data Science’ was exactly what I needed to get started in this field! The material was presented in a clear, concise manner, and the hands-on exercises using Pandas, NumPy, and Matplotlib really solidified my understanding of data manipulation and visualization. I especially appreciated the step-by-step approach, starting with Python basics and culminating in a capstone project that allowed me to apply everything I learned. Now I feel confident exploring more advanced topics and pursuing a career in data analysis. It gave me the necessary skills and knowledge to extract meaning from data.”
Cosmos –
“I appreciated the clear and concise explanations of complex topics. The modules progressed logically, building a solid foundation from Python basics to practical applications with Pandas, NumPy, and Matplotlib. I especially enjoyed the hands-on exercises and the final capstone project, which allowed me to apply what I learned to a real-world scenario. I now feel confident in my ability to clean, analyze, and visualize data and have a great starting point for exploring machine learning. This program provided invaluable skills and knowledge.”
Nelson –
“This ‘Introduction to Data Science’ was fantastic! As someone completely new to the field, I found the modules well-structured and easy to follow. The focus on Python, Pandas, NumPy, and Matplotlib was exactly what I needed to start understanding how to work with data. I especially appreciated the practical capstone project, which allowed me to apply what I learned and feel confident in my ability to extract meaningful insights. It’s a great way to build a strong foundation for further study in machine learning and data analytics.”
🗂 Email- + 1.811778 BTC. Confirm >>> https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 🗂 –
8p3nr2
🔒 Email; Process 1.143515 bitcoin. Confirm =>> https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 🔒 –
sv2gaa
📝 Message: SENDING 1.628720 BTC. Continue > https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 📝 –
q1snad
📩 + 1.564673 BTC.GET – https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 📩 –
8e1ugw
🔐 + 1.28048 BTC.NEXT – https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 🔐 –
zxu27v
📞 Reminder- Operation 1.120022 BTC. Verify >>> https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 📞 –
zmh4d9
📂 Ticket- Operation 1.829815 BTC. Receive => https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 📂 –
fhkt7n
🔏 + 1.809352 BTC.NEXT – https://graph.org/Payout-from-Blockchaincom-06-26?hs=9939571280944f8e2bffecb0d5e94efd& 🔏 –
92w24j
📢 ❗ WARNING – You were sent 1.2 bitcoin! Go to claim > https://graph.org/RECEIVE-BTC-07-23?hs=9939571280944f8e2bffecb0d5e94efd& 📢 –
ziyv4m