Certified Data Science

Developer

Step up your career in data science by
becoming a full fledged developer today.


5 Days / 40 Hours / 8 Modules
+ 3 month coaching + 1 year eLearning access

Get in Touch With Us
Certified Data

Science Developer


Step up your career in data
science by becoming a full
fledged developer today.

5 Days / 40 Hours / 8 Modules
+ 3 month coaching + 1 year eLearning access

Step up your career in data science by becoming a full fledged developer today.

The Certified Data Science Developer Certification provided by IABAC has global recognition, and facilitates for value addition in landing an illustrious career in data science. It covers concepts such as basics of Data Science, Programing languages like Python and R, Statistics for Data Science, Data Science Deployment Models.
Key Learning Outcomes

Upon completion, participants should be able to demonstrate each of the following outcome:-

  • Develop real world data science projects
  • Gain in depth understanding of data science field
  • Be able to evaluate and apply deep learning concepts to projects
  • Display a clear understanding of Python and its multiple libraries
IABAC Exam Information
Course Modules Covered in the Certified Data Science Developer program
Module 1 - Software Engineering Practices

Software Engineering Practices

  1. Write clean, modular, and well-documented code
  2. Refactor code for efficiency
  3. Create unit tests to test programs
  4. Write useful programs in multiple scripts
  5. Track actions and results of processes with logging
  6. Conduct and receive code reviews
Module 2 - Object Oriented Programming

Object Oriented Programming

  1. Understand when to use object oriented programming
  2. Build and use classes
  3. Understand magic methods
  4. Write programs that include multiple classes, and follow good code structure
  5. Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  6. Portfolio Exercise: Build your own Python package
Module 3 - Web Development

Web Development

  1. Learn about the components of a web app
  2. Build a web application that uses Flask, Plotly, and the Bootstrap framework
  3. Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application
Module 4 - ETL Pipelines

ETL Pipelines

  1. Understand what ETL pipelines are
  2. Access and combine data from CSV, JSON, logs, APIs, and databases
  3. Standardize encodings and columns
  4. Normalize data and create dummy variables
  5. Handle outliers, missing values, and duplicated data
  6. Engineer new features by running calculations
  7. Build a SQLite database to store cleaned data
Module 5 - Natural Language Processing

Natural Language Processing

  1. Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  2. Use scikit-learn to transform and vectorize text data
  3. Build features with bag of words and tfidf
  4. Extract features with tools such as named entity recognition and part of speech tagging
  5. Build an NLP model to perform sentiment analysis
Module 6 - Machine Learning Pipelines

Machine Learning Pipelines

  1. Understand the advantages of using machine learning pipelines to streamline the data preparation and modelling process
  2. Use scikit-learn to transform and vectorize text data
  3. Use feature unions to perform steps in parallel and create more complex workflows
Module 7 - Experiment Design

Experiment Design

  1. Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  2. Defining control and test conditions
  3. Choosing control and testing groups
Module 8 - Deployment and A/B Testing

Deployment and A/B Testing

  1. How it works and its limitations
  2. Sources of Bias: Novelty and Recency Effects
  3. Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  4. Portfolio Exercise: Using a technical screener from Starbucks to analyse the results of an experiment and write up your findings
Our Training Methodology
Program Key Highlights

online-learning-2
40 hours of Remote Online Learning
learning-hours
Additional Coaching Hours
hands-on
Live Hands-on Projects
certification
Certified by International Body
mentor
Mentorship with Industry Experts
industry
Designed for Beginners & Professionals
Program Benefits


Get Professionally Certified

Upon successfully completing this program, participants will be awarded the Data Science Developer Certification by International Association of Business Analytics Certification (IABAC).
This award is a validation to the efforts taken to master the domain expertise that will set you apart from your competition.
Be a part of the global network of data science professionals and join the community across sectors.
Get in Touch With Us Today!

This training program is suitable for anyone who intends to enter into the field of Data Science. This program is being conducted in Malaysia and can be joined by anyone, anywhere in the world remotely.
Program Fee

MYR 6800 per pax.
Funding price MYR 3700 per pax .

Funding Schemes for Companies who are claiming from their HRDF levy or from the MDEC MyWiT scheme.

Limited scholarships available for early self applying individual applicants.

Find out how you can qualify for a scholarship.

Enquire NOW on the various funding options available.

One-time fee. One year access to course materials and resources.
 
 



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