Data Science Full Course For Beginners | Python Data Science Tutorial | Data Science With Python
Master Data Science: Your Comprehensive Guide to Python, SQL, Machine Learning & Deep Learning! Explore step-by-step tutorials and projects, from coding fundamentals to advanced algorithms, with codebasics. Unlock your data-driven career today!
4.0
(1)
20 learners
What you'll learn
- Understand the fundamentals of data science and its applications
- Acquire skills in Python programming and data analysis using libraries like Pandas and NumPy
- Develop machine learning models and understand key algorithms such as Linear Regression, Decision Trees, and Neural Networks
- Use deep learning frameworks like TensorFlow and Keras to build and deploy neural network models
This course includes
- 33.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 15 lessons • 33.3 hours of video
"Comprehensive Introduction to Data Science and Python Programming"
15 lessons
• 5.5 hours
"Comprehensive Introduction to Data Science and Python Programming"
15 lessons
• 5.5 hours
- What is Data Science? | Free Data Science Course | Data Science for Beginners | codebasics 06:47
- Data Science Roadmap 2023 | Learn Data Science Skills in 6 Months 48:29
- Business Math & Statistics Using Excel For Data Analysts and Data Scientists 01:24:49
- SQL Tutorial For Beginners | MySQL Tutorial 01:26:10
- What is Jupyter Notebook? | Jupyter Notebook Tutorial in Python 08:25
- What is Anaconda? Install Anaconda On Windows. 05:22
- Jupyter Notebook Tutorial / Ipython Notebook Tutorial 24:08
- Matplotlib Tutorial 1 - Introduction and Installation 06:59
- Matplotlib Tutorial 2 - format strings in plot function 06:18
- Matplotlib Tutorial 3 - Axes labels, Legend, Grid 06:58
- Matplotlib Tutorial 4 - Bar Chart 08:45
- Matplotlib Tutorial 5 - Histograms 08:19
- Matplotlib Tutorial 6 - Pie Chart 06:36
- Data Analyst vs Data Engineer vs Data Scientist 10:52
- Text Classification Using BERT & Tensorflow | Deep Learning Tutorial 47 (Tensorflow, Keras & Python) 18:45
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