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Data Science Courses in Dubai

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Overview

Take your job to the next level in Data Science with the whole training course. We give top-notch Data Science training by Industry Leaders. You will be an expert in the area of Data Science and also learn key technologies consisting of SQL or Oracle, Python, Machine Learning, Deep Learning, Data Visualization, Data visualization and also Artificial Intelligence.

Learning Outcome of Data Science Training:

The Data Science course provides the entire toolbox with the participant's need to become a data scientist.

Statistics: Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction.
R: Learn to program in R, Master R Studio and practice working with statistical data in R.
Data Science and Machine Learning: Get hands-on experience building and deriving insights from machine learning models using R and Microsoft Azure Machine Learning.
Data Visualization: Learn the art and science of data storytelling and achieve greater analytics impact.

After this program, you will:

  • Understand Data Processing and Data Analysis
  • Apply industry-relevant techniques such as Regression, Predictive Modelling, Clustering, Time Series Forecasting, Classification, etc.
  •  Understand data cleaning and data change operations with numerous devices and also techniques
  •  Understand data analytics tools and modern technologies such as Python, Tableau, SQL
  •  Great Expertise in Deep Learning, Natural Language Handling (NLP).
  • Information analysis utilizing different statistics as well as information modelling tools
  • Understand Information Visualization utilizing Tableau or Power BI

Program Content

 

Modules

 

 

Module 1

Database  Engineering Knowledge

Data Preprocessing- Data Wrangling- with (Oracle or MySQL or Cassandra or MariaDB)- overview for the data science

Module 2

Programming Knowledge

Python or  R programming or G programming

Module 3

Machine Learning Knowledge

Supervised learning- Unsupervised learning- Reinforcement Learning

Module4

Deep Learning Knowledge

TensorFlow- Artificial Neural Network- Deep Belief Network- Generative Adversarial Network

Module 5

Big Data Knowledge

Hadoop or Spark

Module 6

Data Visualization Knowledge

Tableau or Power BI or QlikView

 

DATA SCIENTIST / Data Engineer

 

 

 

Module 1  Database Engineering Knowledge (Data Preprocessing- Data Wrangling- with (Oracle or MySQL or Cassandra or MariaDB)- introduction to Data Science.

SQL - MySQL for Data Analytics and Business Intelligence.

What you'll learn.

  •  Learn exactly how to code in SQL.
  • Create, style, and also operate with SQL data sources.
  • Understand SQL finest techniques for Data science.
  • Gain an academic understanding of relational data sources.

Module 2 Programming KnowledgePython or R shows or G shows.

Programming with Python.

What you'll  Learn.

  •  Learn the core concepts of programming.
  • Learn exactly how to create variables.
  • Learn about integer, float, logical, string, and other types in Python.
  • Learn exactly how to produce a while() loop and a for the () loophole in Python.
  • Learn how to mount bundles in Python.
  • Understand the Law of Large Numbers.

Programming with R Programming.

What you'll learn.

  • Learn to program in R at a reasonable level.
  • Learn just how to use R Studio.
  • Learn the core principles of programs.
  • Learn exactly how to produce vectors in R.
  • Learn how to develop variables.
  • Learn about integer, double, logical, personality, and various other enters R.
  • Learn just how to develop a while() loophole and a for() loop in R.
  • Learn exactly how to develop as well as make use of matrices in R.
  • Learn the matrix() feature, discover rbind() and also cbind().
  • Learn exactly how to install packages in R.
  • Learn just how to tailor R studio to fit your choices.

Module 3- Machine Learning Knowledge/ Supervised learning- Unsupervised learning- Reinforcement Learning.

What you'll learn.

  • Deep Learning, Transfer Learning and Neural Networks are using the most up-to-date Tensorflow 2.0.
  • Use modern tools that big tech businesses like Google, Apple, Amazon and Facebook use.
  • Learn ideal techniques when it involves Data Science Workflow.
  • Implement Machine Learning algorithms.
  • Learn to pre-process information, clean information, and also examine comprehensive data.
  • Developer Environment configuration for Data Science as well as Machine Learning.
  • Supervised as well as Unsupervised Learning.
  • Machine Learning promptly Series information.
  • Learn NumPy and just how it is used in Machine Learning.
  • A portfolio of Data Science and Machine Learning jobs to request work in the industry with all code and note pads provided.

Module4-Deep Learning KnowledgeTensorFlow- Artificial Neural Network- Deep Belief Network- Generative Adversarial Network.

What you'll learn.

  • Understand the logic behind Artificial Neural Networks.
  • Apply Artificial Neural Networks in practice.
  • Understand the impulse behind Convolutional Neural Networks.
  • Apply Convolutional Neural Networks in the method.
  • Understand the intuition behind Recurrent Neural Networks.
  • Apply Recurrent Neural Networks in the technique.

Module 5- Big Data Knowledge (Hadoop or Spark.)

What you'll learn.

  •  Use DataFrames as well as Structured Streaming in Spark 3.
  • Use the MLLib machine learning library to answer usual data mining questions.
  • Understand how Spark Streaming lets your procedure constantly stream data in real-time.
  • Frame big data evaluation troubles as Spark troubles.
  •  Install and run Apache Spark on a desktop or a collection.
  • Use Spark's Resilient Distributed Datasets to process as well as examine massive information sets throughout lots of CPU's.
  • Implement repetitive algorithms such as breadth-first-search utilizing Spark.
  • Understand how Spark SQL lets you collaborate with organized information.
  • Share info between nodes on a Spark cluster using broadcast variables and accumulators.

Module 6 Data Visualization Knowledge.

Data Visualization using Tableau.

What you'll learn.

  • Connect Tableau to different Datasets: Excel and CSV documents.
  • Work with Data Blending in Tableau.
  • Work with Parameters.
  • Export Results from Tableau into Powerpoint, Word, and other software applications.
  • Work with Timeseries Data (2 approaches).
  • Creating Data Extracts in Tableau.
  • Adding Actions to Dashboards (filters & highlighting).
  • Advanced-Data Preparation (including the newest updates in Tableau).

Data Visualization using Power BI.

What you'll learn.

  • Understand the features of Power BI
  • Learn complete concepts that consist of Report Designing, Visual Sync, Grouping, Hierarchies, Filters, Bookmarks, Azure, Modeling, DAX Functions - Level 1, DAX Functions - Level 2, Power BI Cloud, Excel & RLS, Report Server, RDL and more.

Data Visualization is utilizing QlikView.

What you'll learn.

  •  Learn about different Design Schema types.
  • Find out to code Joins & understand precisely how they work.
  • Find out how to pack and link to various data sources (e.g. SQL, Web ).
  • Code Scripts for ETL information handling.
  • Produce Graphes such as Gauges, Pie, Bar, Combo, Line, Hurricane, Warm Maps, and Scatter.
  • Find out performance adjusting for graphs and also scripting.
  • Apply your brand-new skills to QlikSense, e.g. Modelling, Establish Evaluation.

Data Science Certifications

DASCA- Data Science Council of America    Data Engineer       Associate    Associate Big Data Engineer
DASCA   Non-Technical (For Marketing)       Associate    Associate Big Data Analyst


Data Scientist  Professional    Senior Data Scientist
Microsoft         
  Data Analyst beginner
Exam DP 900: Microsoft Azure Data Fundamentals
    Beginner
Microsoft certified Azure Data Fundamentals Exam DP-900
  Data Analyst Associate
Microsoft certified: Data Analyst Associate Exam DA-100
  Data Engineer Data Engineer Microsoft Certified: Azure Data Engineer Associate
Requirements: Exam DP-200, DP-201

Azure Data Engineers integrate, transform, and consolidate data from various structured and unstructured data systems into structures that are suitable for building analytics solutions.
  Data Scientist  
Microsoft Certified: Azure Data Scientist Associate
Requirements: Exam DP-100
The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service.
     
Microsoft’s MCSE- Data Management and Analytics
SAS    
Big Data Professional Using SAS 9 Certification
Cloudera Data Analyst Cloudera certified
Associate
Associate
CCA Data Analyst
  Developer associate
CCA Spark and Hadoop Developer
     
Zabeel certified can do - 18 hrs without lab
  Data Engineer Professional
CCP Data Engineer Exam
AWS Cloud Data Analytics Speciality AWS Certified Data Analytics

Zabeel Certified
    Big Data and Data Science

 

Zabeel Institute is considered as the best training institute in Dubai for the Data Science courses.

 

Data Science with R

Zabeel offers highly professional data science courses in Dubai, Sharjah -UAE, Aspiring data scientists, data analyst, technologists, software developers, academics and students.

We are a fully accredited Institute by KHDA and endorsed by students as the Best Data Science Course training institute in Dubai.

Zabeel offers data science training in Dubai and a data scientist course in Dubai. We are one of the Top ranking training institutes in Dubai. 

To know more about data science courses in Dubai, please click here.

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About Certification and Awarding Body

Course completion certificate from Zabeel Institute of Management & Technology will be provided.

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