Big Data Series – Learn Data Science, Statistics and Machine Learning using Python
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The rushed lunch breaks weren't happy but the experience of the class was great for the mixed one.
← | →
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The agile course is effective and helpful for applying to new practices.
← | →
Short course
Inhouse
Description
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Type
Short course
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Level
Intermediate
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Methodology
Inhouse
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Duration
4 Days
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Start date
Different dates available
Designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science, this course’s content can be adjusted based on student experience level with Python to include full overview of Python and programming if necessary.The course can be adjusted to be between 3-5 days, depending on desired student outcomes and student experience when delivered as a group in house program.
Facilities
Location
Start date
Start date
About this course
Students wanting to use Python for Data Science and Statistical Analysis
This course is designed for beginners and those with some programming experience.
This course contains numerous hands on exercises to build your Advanced skillset.
Reviews
-
The rushed lunch breaks weren't happy but the experience of the class was great for the mixed one.
← | →
-
The agile course is effective and helpful for applying to new practices.
← | →
Course rating
Recommended
Centre rating
Jacob Joshua
Corlous Bravo
This centre's achievements
All courses are up to date
The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 6 years
Subjects
- Statistics
- Programming
- Metadata
- Cloud
- Data Analytics
- MongoDB
- R Programming
- HIVE
- Pig
- Cluster computing
Teachers and trainers (1)
Bright Solutions
Trainer
Course programme
Learn how to program with Python
How to create amazing data visualizations
How to use Machine Learning with Python
Programming with Python
NumPy with Python
Use matplotlib and Seaborn for data visualizations
Web scraping with Python
Using pandas Data Frames to solve complex tasks
Use pandas to handle Excel Files
Connect Python to SQL
Use plotly for interactive visualizations
Machine Learning with SciKit Learn
and much more!
By the end of this course training students will be able to:
Comfortably program with Python
Use Python and pandas to read data from a variety of sources (SQL, Excel, CSV, HDFS, etc)
Use multiple libraries to create data visualizations
Use Python’s SciKit Learn library to implement Machine Learning Models
Understand how to use Spark to deal with big data and distributed systems
Big Data Series – Learn Data Science, Statistics and Machine Learning using Python