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Join us in this enlightening journey towards becoming a Data Scientist and discover the potential of data in making informed decisions. Your path to data expertise begins here.
Course Price:
Original price was: £194.00.£19.99Current price is: £19.99.
Course Duration:
9 hours, 46 minutes
Total Lectures:
62
Total Students:
41
Average Rating:
4.5
Embark on your journey to become a proficient Data Scientist with our comprehensive course. Learn the fundamental tools and techniques required to excel in the world of data science. This course covers essential topics, including Pandas for data science, numpy basics, and data visualization with a focus on Seaborn. By the end of this course, you'll be well-equipped to tackle real-world data challenges with confidence.
What Will You Learn?
- Gain a strong foundation in data science.
- Master data manipulation using Pandas.
- Understand the core concepts of numpy for efficient data handling.
- Explore data visualization techniques to convey insights effectively.
- Harness the power of Seaborn for advanced data visualization.
Who Should Take The Course?
- Aspiring data scientists looking to kickstart their career.
- Professionals in fields like analytics, business intelligence, or research seeking to enhance their data skills.
- Anyone interested in exploring the exciting world of data science and visualization.
Requirements
- A basic understanding of Python is recommended.
- Access to a computer with Python and relevant libraries installed.
- Enthusiasm and a passion for working with data.
Course Curriculum
-
- Introduction – Why are you here and what we will accomplish here 00:01:00
- What are the prerequesits for data science and this course 00:02:00
- Check you system 00:05:00
-
- All you need to know about Series 00:23:00
- Pandas for data scientists – 1 00:07:00
- Pandas for data scientists -2 00:05:00
- Pandas for data scientists – 3 00:06:00
- Pandas for data scientists – 4 00:08:00
- Broadcasting operations 00:07:00
- Counting 00:05:00
- The issue with missing values – a common problem in machine learning 00:10:00
- Dealing with missing values 00:10:00
- The right data in the right format 00:06:00
- Sorting your data properly 00:06:00
- How to slice your data 1 00:06:00
- How to slice your data 2 00:05:00
- How to check for missing values 00:04:00
- A machine learning insight – a full case study 00:25:00
- Master dates 00:11:00
- How to deal with dublicates 00:06:00
- How to play with the Index 00:07:00
- Slicing techniques 00:11:00
- Slicing techniques 2 00:21:00
- More data science techniques in pandas 00:11:00
- Data querying in pandas 00:06:00
- How to work with dates 00:26:00
- How to work with dates 2 00:03:00
- How to work with dates 3 00:05:00
- How to work with dates 4 00:03:00
- Grouping in pandas beginner to advanced 00:17:00
- The Multiindex 00:19:00
- Data science and Finance 00:26:00
- In depth combining dataframes 00:31:00
- Useful ways to deal with strings (regex example) 00:15:00
- Bonus Tips and Tricks 00:09:00
- Bonus Tips and Tricks 2 00:07:00
- Bonus Tips and Tricks 3 00:11:00
- What are Tensors 00:08:00
- Introduction to numpy 1 00:06:00
- Introduction to numpy 2 00:10:00
- Introduction to numpy 3 00:09:00
- Introduction to numpy 4 00:12:00
- Seaborn introduction 00:01:00
- How to master seaborn 1 00:05:00
- How to master seaborn 2 00:05:00
- How to master seaborn 3 00:05:00
- How to master seaborn 4 00:03:00
- How to master seaborn 5 00:05:00
- How to master seaborn 6 00:06:00
- How to master seaborn 7 00:03:00
- How to master seaborn 8 00:05:00
- How to master seaborn 9 00:05:00
- How to master seaborn 10 00:06:00
- How to master seaborn 11 00:02:00
- How to master seaborn 00:02:00
- How to master seaborn 00:03:00
- How to master seaborn 00:03:00
- The end of the road – What to do now 00:01:00
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