Python for Analytics

Track: Associate Enterprise Data Analyst (AEDA)

This module will empower students to write a workable program to solve data related problem using Python’s powerful data processing libraries. This is hallmark of advanced ability for professionals.

Duration: 5 days
Fee: Request
Start Date: Request

Tame Your Data With Python

Students will learn how to leverage the rich ecosystem of libraries provided by the open source community that enables automation and analysis of data on a large scale. In this module, the students will become versed in Python libraries to transform data in the form of both numeric tables and text, visualize data and how to write an end-to- end program.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;

Understand the advantages and possibilities of Python’s data processing libraries
Comprehend the principles, techniques and practices relevant to Python programming using the libraries relevant to data processing
Design and solve more advanced data- related problems by writing a workable program using Python libraries

Who should attend:

Analysts and business professionals who want to jumpstart their abilities in analyzing data

5 days of in depth learning

Face to face with experienced Data Scientist.

Course Methodology

This course will utilize a combination of Lectures and Hands-on Exercises.

CADS Certification

Earn certification upon completion.

Pre-requisite:
N/A

Minimum Qualification:
Undergraduate Degree

Training Track

Associate Enterprise Data Analyst (AEDA)

Python for Analytics is one of the modules under our Associate Enterprise Data Analyst (AEDA) programme. AEDA is a 13 to 18-day training program that provides analysts with the tools required for efficient Data Analysis.

Details of Subject

Data Wrangling with Numpy & Pandas – Numpy and Pandas are the cornerstone of doing data wrangling in Python. Participants will first learn how to manipulate data in Numpy arrays, an efficient data structure for numerical computation. Subsequently, students will learn how to manipulate data using Pandas, a library built on top of Numpy. Learning Pandas will enable students to perform various data wrangling tasks such as loading, sub-setting and transforming data using its sophisticated data structure. This will equip students with the knowledge to use the essential tool for data preparation.
Data Visualization with Matplotlib & Seaborn – Participants will learn how to create various charts and modify the chart components and objects using the Matplotlib package. Having acquired some basic understandings of Matplotlib, students will be taught how to use the Seaborn library, a package built on top of Matplotlib framework to quickly create beautiful charts.
Running Python from Command Line – Participants will learn how to execute Python scripts from command line. This entails getting familiar with the typical structure and arguments of Python scripts. Students will also work on an exercise of writing a Python script that performs data cleaning and running it from the command line.

Lead Instructor

Jan Sauer

Jan Sauer was a biostatistician in the field of deep learning and image/pattern recognition. He has a master’s degree in physics and have extensive experience as a software developer. Throughout his career, he has been involved in different areas of data science, ranging from automated data collection and data analysis, data pipeline and database design, and advanced machine learning where he uses Tensorflow extensively in image processing.

CADS Certification

AEDA CADS Certified Python for Analytics

Python has become a key driver in the explosion of big data analytics and machine intelligence across most industries. Given its versatility and applicability to data analysis, it has become the tool of choice for most industries. Put your fluency in Python through its paces and watch it pay off long-term in spades. This certification will require knowledge in data types, collections, function and control structures, use of python libraries to manipulate and visualize data and writing of workable end-to-end code.

Hear from Our Alumni

The training has benefited me a lot with the skills required to be a data analyst and has upskilled me in data analysis. What I like about the program is where real life problems in the office is used as the materials during the trainings which provides more understanding of the topics. Eventually, it has broaden up my market in the career development.

The program started by setting an expectation on Day 1, that it is not a Read-And-Pass syllabus. The beauty of this program is that it requires the trainees to get their hands dirty and do the actual work throughout the course. It is indeed very different from a lot of programs in the market which just produces a certificate in the end without the trainee actually able to do some real stuff. The course is definitely benefiting anyone who really want to do Machine Learning and Data Science, by creating talents who are able to connect human thought with the machine algorithm, being the bridge within the corporate, into the digital worlds.

The training was beneficial as it trains myself to think from another perspective - one that may not be new, but wasn't practiced as often as I'd like. It was fun and interactive thanks to the facilitator, Jay, too. He was very helpful to answer any questions the attendees have. Believe that this training gives the attendees an extra edge by giving them the knowledge and perspective on how to better utilize data to what they want/need to do - for the organization, the business, and even for personal use, of which I believe will bring myself further in my career.

The training has been an eye opener for me. As someone who is not of programming background, it introduces me to the possibilities of what data can do. It has also helped me bridge the difference in thinking between the Business Team and the Data Science Team. Had a great time learning!

This training enhance on my skill of analyzing of using another tools of programming instead of excel and how to model and visualized our data in a better way instead of our traditional way. Especially when involve with a large scale of data. If using excel, there will a lot of time consuming there instead of R. For me, in market nowadays of big data, this course will brings more value and create another point of view on how to visualize our data especially in making any decision. And of course will enhance our career development.

Register Interest

Python for Analytics

Python for Analytics

Tame Your Data With Python

Learning outcome: