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Overview
By enroling in Python Data Science, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.
The Python Data Science course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Python Data Science course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Python Data Science Program.
So enrol in our Python Data Science course right away if you’re keen to envision yourself in a rewarding career.
Description
Enroling in this Python Data Science course can improve your Python Data Science perspective, regardless of your skill levels in the Python Data Science topics you want to master. If you’re already a Python Data Science expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Python Data Science insights that will help you make the most of your time. This Python Data Science course will act as a guide for you if you’ve ever wished to excel at Python Data Science.
Why Choose Us?
- This course is accredited by the CPD Quality Standards.
- Lifetime access to the whole collection of the learning materials.
- Online test with immediate results.
- Enroling in the course has no additional cost.
- You can study and complete the course at your own pace.
- Study for the course using any internet-connected device, such as a computer, tablet, or mobile device.
Certificate of Achievement
Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99.
Who Is This Course For?
This Python Data Science course is a great place to start if you’re looking to start a new career in Python Data Science field. This training is for anyone interested in gaining in-demand Python Data Science proficiency to help launch a career or their business aptitude.
Requirements
The Python Data Science course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Python Data Science, without any fuss.
Career Path
This Python Data Science training will assist you develop your Python Data Science ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a Python Data Science professional story and personalise your path to a new career. Furthermore, developing this Python Data Science skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.
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Course Curriculum
| Course Introduction and Table of Contents | |||
| Course Introduction and Table of Contents | 00:09:00 | ||
| Introduction to Python, Pandas and Numpy | |||
| Introduction to Python, Pandas and Numpy | 00:07:00 | ||
| System and Environment Setup | |||
| System and Environment Setup | 00:08:00 | ||
| Python Strings | |||
| Python Strings – Part 1 | 00:11:00 | ||
| Python Strings – Part 2 | 00:09:00 | ||
| Python Numbers and Operators | |||
| Python Numbers and Operators – Part 1 | 00:06:00 | ||
| Python Numbers and Operators – Part 2 | 00:07:00 | ||
| Python Lists | |||
| Python Lists – Part 1 | 00:05:00 | ||
| Python Lists – Part 2 | 00:06:00 | ||
| Python Lists – Part 3 | 00:05:00 | ||
| Python Lists – Part 4 | 00:07:00 | ||
| Python Lists – Part 5 | 00:07:00 | ||
| Tuples in Python | |||
| Tuples in Python | 00:06:00 | ||
| Sets in Python | |||
| Sets in Python – Part 1 | 00:05:00 | ||
| Sets in Python – Part 2 | 00:04:00 | ||
| Python Dictionary | |||
| Python Dictionary – Part 1 | 00:07:00 | ||
| Python Dictionary – Part 2 | 00:07:00 | ||
| NumPy Library - Introduction | |||
| NumPy Library Intro – Part 1 | 00:05:00 | ||
| NumPy Library Intro – Part 2 | 00:05:00 | ||
| NumPy Library Intro – Part 3 | 00:06:00 | ||
| NumPy Array Operations and Indexing | |||
| NumPy Array Operations and Indexing – Part 1 | 00:04:00 | ||
| NumPy Array Operations and Indexing – Part 2 | 00:06:00 | ||
| NumPy Multi-Dimensional Arrays | |||
| NumPy Multi-Dimensional Arrays – Part 1 | 00:07:00 | ||
| NumPy Multi-Dimensional Arrays – Part 2 | 00:06:00 | ||
| NumPy Multi-Dimensional Arrays – Part 3 | 00:05:00 | ||
| Introduction to Pandas Series | |||
| Introduction to Pandas Series | 00:08:00 | ||
| Introduction to Pandas Dataframes | |||
| Introduction to Pandas Dataframes | 00:07:00 | ||
| Pandas Dataframe conversion and drop | |||
| Pandas Dataframe conversion and drop – Part 1 | 00:06:00 | ||
| Pandas Dataframe conversion and drop – Part 2 | 00:06:00 | ||
| Pandas Dataframe conversion and drop – Part 3 | 00:07:00 | ||
| Pandas Dataframe summary and selection | |||
| Pandas Dataframe summary and selection – Part 1 | 00:06:00 | ||
| Pandas Dataframe summary and selection – Part 2 | 00:06:00 | ||
| Pandas Dataframe summary and selection – Part 3 | 00:07:00 | ||
| Pandas Missing Data Management and Sorting | |||
| Pandas Missing Data Management and Sorting – Part 1 | 00:07:00 | ||
| Pandas Missing Data Management and Sorting – Part 2 | 00:07:00 | ||
| Pandas Hierarchical-Multi Indexing | |||
| Pandas Hierarchical-Multi Indexing | 00:06:00 | ||
| Pandas CSV File Read Write | |||
| Pandas CSV File Read Write – Part 1 | 00:05:00 | ||
| Pandas CSV File Read Write – Part 2 | 00:07:00 | ||
| Pandas JSON File Read Write | |||
| Pandas JSON File Read Write Operations | 00:07:00 | ||
| Pandas Concatenation Merging and Joining | |||
| Pandas Concatenation Merging and Joining – Part 1 | 00:05:00 | ||
| Pandas Concatenation Merging and Joining – Part 2 | 00:04:00 | ||
| Pandas Concatenation Merging and Joining – Part 3 | 00:04:00 | ||
| Pandas Stacking and Pivoting | |||
| Pandas Stacking and Pivoting – Part 1 | 00:06:00 | ||
| Pandas Stacking and Pivoting – Part 2 | 00:05:00 | ||
| Pandas Duplicate Data Management | |||
| Pandas Duplicate Data Management | 00:07:00 | ||
| Pandas Mapping | |||
| Pandas Mapping | 00:04:00 | ||
| Pandas Grouping | |||
| Pandas Groupby | 00:06:00 | ||
| Pandas Aggregation | |||
| Pandas Aggregation | 00:09:00 | ||
| Pandas Binning or Bucketing | |||
| Pandas Binning or Bucketing | 00:08:00 | ||
| Pandas Re-index and Rename | |||
| Pandas Re-index and Rename – Part 1 | 00:04:00 | ||
| Pandas Re-index and Rename – Part 2 | 00:05:00 | ||
| Pandas Replace Values | |||
| Pandas Replace Values | 00:05:00 | ||
| Pandas Dataframe Metrics | |||
| Pandas Dataframe Metrics | 00:07:00 | ||
| Pandas Random Permutation | |||
| Pandas Random Permutation | 00:08:00 | ||
| Pandas Excel sheet Import | |||
| Pandas Excel sheet Import | 00:07:00 | ||
| Pandas Condition Selection and Lambda Function | |||
| Pandas Condition Selection and Lambda Function – Part 1 | 00:05:00 | ||
| Pandas Condition Selection and Lambda Function – Part 2 | 00:05:00 | ||
| Pandas Ranks Min Max | |||
| Pandas Ranks Min Max | 00:06:00 | ||
| Pandas Cross Tabulation | |||
| Pandas Cross Tabulation | 00:07:00 | ||
| Matplotlib Graphs and plots | |||
| Graphs and plots using Matplotlib – Part 1 | 00:06:00 | ||
| Graphs and plots using Matplotlib – Part 2 | 00:02:00 | ||
| Matplotlib Histograms | |||
| Matplotlib Histograms | 00:03:00 | ||
| Order Your Certificate | |||
| Order Your Certificate | 00:00:00 | ||
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