Artificial Intelligence and Data Science

Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data […]

Updated February 7, 2023

About Course

Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.

However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.

And how can you do that?

Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming)

Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture

The Solution

Data science is a multidisciplinary field. It encompasses a wide range of topics.

  • Understanding of the data science field and the type of analysis carried out
  • Mathematics
  • Statistics
  • Python
  • Applying advanced statistical techniques in Python
  • Data Visualization
  • Machine Learning
  • Deep Learning

Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is.

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What Will You Learn?

  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations

Course Content

Module ( 1 )

  • Introduction to AI
  • History of Artificial Intelligence
  • Artificial Intelligence (AI) vs. Machine Learning (ML) vs. Deep Learning (DL)
  • AI Applications
  • AI Basics
  • The benefits of Artificial Intelligence
  • Future of Artificial Intelligence
  • How Do Big Data and Data Analytics Change IT Analysis
  • The Business Analyst Role in Implementing AI-Based Business Solutions
  • The Impact of AL in Three Level of Business Analysis
  • Targeted IT Business Analysis: Analyze Features and User Stories
  • Tactical Business Analysis: Elicit and Prioritize User Requirements
  • Strategic Business Analysis: Prepare for Future Changes

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Module ( 13 )

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Artificial Intelligence and Data Science
Duration 30 hours
162 Lessons

Material Includes

  • After passing the related Bootcamp requirements ( Exam, or Research, Capstone project ) attendees will be qualified to get Certification of achievements Name will be : Global Certified AI Data Scientist ( GCAI | DS )


  • NA


  • You should take this course if you want to become a Data Scientist or if you want to learn about the field
  • This course is for you if you want a great career
  • The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
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