Data Science & Python: Maths, Python Libraries, Statistics
Learn Python, data science tools, and algorithms in this comprehensive course. Gain insights from raw data to make informed business decisions.
What you’ll learn
- What is Python
- Uses of Python
- How to write code in Python
- What are Python libraries
- What is Anaconda
- What is Jupyter Notebook
- What is Numpy
- What is Matplotllib
- How to plot in Matplotlib
- What is Scipy
- What is Scikit
- What is Pandas
- How to import files in Jypyter notebook using Pandas
- How to create files using Pandas
- Basic math in Python
- Linear Algebra in Pythom
- Statistics in Python
- 2d and 3d plotting in Python
- Linear regression in Python
- differential and Integral calculus in Python
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Get instant access to a 73-page workbook on Data Science, follow along, and keep for reference
Introduce yourself to our community of students in this course and tell us your goals with data science
Encouragement and celebration of your progress every step of the way: 25% > 50% > 75% & 100%
Over 13 hours of clear and concise step-by-step instructions, lessons, and engagement
This data science course provides participants with the knowledge, skills, and experience associated with Data Science. Students will explore a range of data science tools, algorithms, linear programming and statistical techniques, with the aim of discovering hidden insights and patterns from raw data in order to inform scientific business decision-making.
What you will learn:
Introduction to Python; what is Python, Anaconda, libraries, Numpy, Matplotlib, SciPy and SciKit Learn
Learn mathematics by coding in python; basic maths, variables. solutions of equations. logarithmic and exponential functions. polynomials, complex numbers and trigonometry
Statistics by coding in Python
Linear Algebra for data science: matrices. determinants, inverse, solutions, scalars and vectors
Detailed introduction and demo of Numpy
Linear algebra in Python as well as calculus. Matplotlib and more
Lear Data Science projects in Pandas: importing files, creating data frames
Regression analysis using SKLearn
Data science careers in a Q&A Webinar plus additional insights; learn from other students questions
Who are the Instructors?
Dr. Allah Dittah is your lead instructor – a PhD and lecturer making a living from teaching Python, advanced mathematics and data science. As a data science expert, he has joined with content creator Peter Alkema to bring you this amazing new course.
You’ll get premium support and feedback to help you become more confident with data science!
We can’t wait to see you on the course!
Enrol now, and we’ll help you improve your data science skills!
Peter and Allah
Who this course is for:
- For those who love with learning
- Data scientists
- For those who want to apply Python in a practical way in their organization
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