Data Analytics Specialization

Acquire essential data analysis skills and land a top job in the field of Data.
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Benefits of becoming
part of our community

Embark on a transformative educational journey alongside like-minded individuals through our innovative online, part-time programs designed to elevate your learning experience.

Flexible Learning

Our programs offer a combination of self-paced coursework and live sessions with industry professionals to clarify concepts and enhance your understanding.

Convenient Schedule

Enjoy the flexibility of our part-time, online program to fit your busy life and commitments.

Instructor-Led Cohort

Join a cohort led by expert instructors who provide guidance, support, and valuable insights throughout your learning experience.

Hands-On Projects

Engage in practical capstone projects, either self-designed or in collaboration with industry partners, to showcase your skills.

Collaborative Cohort

Stay motivated and inspired by the support of your cohort peers and our dedicated team throughout your learning journey.

Career Support

Access exclusive career services, including career fair, interviews, projects, and sourcing opportunities, to accelerate your career growth.

PROGRAM SCHEDULE

Data Analytics Foundations

Skills Gained

  • Proficiency in R programming language, specifically in using Jupyter Notebooks.
  • Understanding of tidyr package for manipulating and analyzing tabular data
  • Familiarity with the data analysis process, including data collection, data cleaning, exploratory data analysis, and data visualization.
  • Ability to conduct EDA using tidyverse, ggplot2 and other libraries in R.

Learning Outcomes

This module aims to introduce you to the fundamentals of data analysis using R programming language and popular packages like tidyr and ggplot2. By the end of this module, you should have a basic understanding of how to manipulate, analyze, and visualize data using R.

Data Analytics with Excel

Skills Gained

  • Ability to explore data using Excel's built-in features like filtering, sorting, and conditional formatting
  • Understanding of different data types and how to work with them in Excel
  • Knowledge of data cleaning techniques, including removing duplicates, and formatting data
  • Ability to prepare data for analysis, including reshaping data and using formulas and functions

Learning Outcomes

This module aims to teach you the fundamentals of data analysis using Microsoft Excel. By the end of this module, you should be able to use Excel to explore, clean, prepare, and analyze data.

Statistical Based Analysis

Skills Gained

  • Understanding of probability, distributions, and the central limit theorem
  • Ability to interpret confidence intervals
  • Familiarity with hypothesis testing and A/B testing
  • Knowledge of linear and logistic regression and their applications to data analysis.

Learning Outcomes

The goal of this module is to provide a comprehensive understanding of statistical analysis concepts and techniques, including probability, distributions, central limit theorem, and much more.

Data Wrangling with R

Skills Gained

  • Ability to import and export data in various formats using R
  • Proficiency in assessing data quality and identifying data issues
  • Knowledge of various data cleaning techniques and the ability to apply them using R
  • Ability to transform data into a format suitable for analysis using R.

Learning Outcomes

In this module, you will gain the necessary skills to effectively gather, assess, clean, and transform data using R. These skills will help you handle real-world data challenges and prepare data for analysis.

Exploring Databases

Skills Gained

  • Understanding of databases and their importance
  • Knowledge of the different types of databases
  • Ability to distinguish between relational and non-relational databases
  • Basic understanding of SQL and its usage in database querying and manipulation.

Learning Outcomes

In this module, you will learn about databases, their types, and their importance in the world of data. You will gain an understanding of relational and non-relational databases, and learn the basics of SQL.

Storytelling with Data

Skills Gained

  • Choosing the appropriate type of graph for your situation
  • Recognizing the clutter clouding your information
  • Tips and tricks for a successful presentation
  • Understanding the audience and their needs
  • Utilizing business intelligence tools to build an effective story

Learning Outcomes

The goal of this module is to teach you how to effectively communicate insights and patterns in your data through various types of visualizations such as univariate, bivariate, and multivariate plots. You will also discover tools and techniques to create an engaging and informative story. In order to achieve this, you will explore some business intelligence tools such as Tableau and Power BI.

OUR ALUMNI

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Wissam Moussa

Changing career and becoming a Machine Learning Engineer in 16 weeks
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Fatima Ksayrawi

From 0 knowledge in Machine Learning to a Machine Learning Engineer
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Hassan Kanaan

From Software Engineering to Machine Learning Engineer

ENROLLMENT PROCESS

01

INTERVIEW

Go through a general interview to make sure that the program is the right fit for you.

02

ACCEPTANCE

Receive an official acceptance for enrollment.

How Does The Certification Program
Prepare You For The Job Market?

  • Master fundamental concepts and the language of Data Analytics
  • Learn how to best represent yourself to recruiters in the Data Analytics space
  • Work in a team to solve a real-world, research-oriented challenge
  • Gain the skills to become a sufficient self-learner and investigator in the field of Data Analytics
  • Learn the best practices for Data Analytics in development and in research settings
  • Be guided by AI instructors and engineers to learn from real-life practitioners
  • Gain the soft skills to become a full-stack fit in a diverse Data Analytics team in the job market

PRICE

PER PERSON

$2,967

Different financing options available

  • Recorded sessions including lectures and coding labs
  • Live instructor-led online workshops
  • Learn from others: invited online talks & discussions
  • Weekly office hours & round-the-clock advising
  • Group capstone project with guided mentorship
  • Career development workshops & mentorship
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