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Discover a diverse range of Data Science courses in Dubai tailored to meet your educational needs. Explore accredited programs, expert instructors, and flexible learning options to excel in your chosen field. Enroll today and embark on a transformative educational journey.
By: Simpliv Llc
ABOUT THE COURSE
Want to learn all the elements of Tableau Desktop 10? You have come to the right place. Simpliv’s Tableau Certification Training will familiarize you with everything about Tableau, including visualizing, data organization and dashboard designing. Our course will ensure that you also don’t get left out of other concepts of Tableau, such as mapping, data connection and statistics. Ideal for system administrators, business intelligence professionals and software developers, Simpliv is all geared to put you on the road to Tableau Desktop 10 Qualified Associate certification.
Who is the target audience?
All the professionals who are passionate about business intelligence, data visualization, and data analytics.
Basic knowledge:
There are no prerequisites for taking up this certification training course.
Curriculum
Visualization with Tableau
Price: ââ¹ 16665 ( Enroll Today and Get Flat 40% OFF )
New Batch starts from 11th Feb 2019 Days: Mon-Fri (10 Days) 07:00 PM - 10:00 PM (IST)
By: Simpliv Llc
Prerequisites: Working with HBase requires knowledge of Java
Record and run settings a team which includes 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing jobs.
Relational Databases are so stuffy and old! Welcome to HBase - a database solution for a new age.
HBase: Do you feel like your relational database is not giving you the flexibility you need anymore? Column-oriented storage, no fixed schema and low latency make HBase a great choice for the dynamically changing needs of your applications.
What's Covered:
25 solved examples covering all aspects of working with data in HBase
CRUD operations in the shell and with the Java API, Filters, Counters, MapReduce
Implement your own notification service for a social network using HBase
HBase and it’s role in the Hadoop ecosystem, HBase architecture and what makes HBase different from RDBMS and other Hadoop technologies like Hive.
Using discussion forums
Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(
We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.
The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.
We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.
It is a hard trade-off.
Thank you for your patience and understanding!
Who is the target audience?
BASIC KNOWLEDGE
WHAT YOU WILL LEARN
By: G- Tec Education Institute Dubai
G-TEC is an ISO certified organization in the noble field of education in various segments including ICT, Academic programs, Robotics, ITeS, Corporate trainings, Skilling and vocational trainings including Government projects through quality training centres. G-TEC is one of the world’s largest education network with 600+ training centres in 15+ countries and is reputed for its quality, brand and vendor certification.
Data Science Training Program
Course description
Data science can be defined as a blend of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions. In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics in them. Thus, data science is all about the present and future. That is, finding out the trends based on historical data which can be useful for present decisions and finding patterns which can be modelled and can be used for predictions to see what things may look like in the future. Data Science is an amalgamation of Statistics, Tools and Business knowledge. So, it becomes imperative for a Data Scientist to have good knowledge and understanding of these.
Course outline
The following topics will be covered by this introductory course:
· Introduction and Importance of Data Science
· Statistics
· Information Visualisation
· Data Mining, Data Structures, and Data Manipulation
· Algorithms used in Machine Learning
· Data Scientist Roles and Responsibilities
· Data Acquisition and Data Science Life Cycle
· Deploying Recommender Systems on Real-World Data Sets
· Experimentation, Evaluation and Project Deployment Tools
· Predictive Analytics and Segmentation using Clustering
· Applied Mathematics and Informatics
· Working on Data Mining, Data Structures, and Data Manipulation
· Big Data Fundamentals and Hadoop Integration with R
By: 361 Degree Minds Consulting Pvt Ltd
This Post Graduate Program in Business Analytics – designed by veterans in the Analytics industry; helps to establish a decent career in the growing Data and Analytics domain. This uniquely blended Program is brought to by Praxis, a Top-ranked Analytics B-School in India. Post Graduate Program in Business Analytics is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 12-15 months of faculty led Online mode. The following are the modules covered" Big Data 101 Big Data Characteristics Big Data and Business Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms Clustering Algorithms – UPGMA, single Link Clustering KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding Mathematics Modelling Introduction to key mathematical concepts Application of eigenvalues and eigenvectors Application of the graph Laplacian Application of PCA and SVD Coding in DB Environment Making Data Sets R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Text Analytics Basics of text analysis processes Web crawling Web Scraping from downloaded html files Text classification Singular Value decomposition concept Latent Semantic Analysis Document clustering Topic Modeling Class Assignments Presentation Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I Measures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III Python Understanding Basics of Python Control Structures and for loop Playing with while loop | break and continue Strings and files List Dictionary and Tuples Statistics with R Introduction to Data Introduction to Probability Distributions Introduction to linear regression Foundations for inference and estimation Foundations for inference and hypothesis testing Linear Regression and Multiple Regression Data Mining 1 - Machine Learning with R & Python Introduction to NumPy Introduction to Pandas Slicing Data Exploratory Data Analysis Exploratory Data Analysis (Continue) Missing Value Imputation and Outlier Analysis Linear Regression Motivation Linear Regression optimization objective Linear Regression in Python Introduction to Regression Tree Introduction to Classification Tree Measures of Selecting the best Split Cluster Analysis – Hierarchical Clustering & k-Means Clustering Customer segmentation in Telecom Industry using Cluster Analysis k-Means clustering Association Rules mining Market Basket Analysis Advanced Statistics with R Inference and hypothesis testing on single population Analysis of difference in two populations Analysis of Variance Chi-Square Analysis Analysis of data using Non-parametric Statistics Linear regression analysis Multiple regression analysis Advanced Multiple regression analysis Logistic Regression Forecasting Data Visualization with Tableau Need for visualizing data Research methodologies Importance of Big data visualization Tableau product offerings Installation of Tableau Public Working with Tableau - Live Case study/Discussion Creating interactive dashboards with Tableau Public Case study discussion Story Boarding with Tableau Public Case study discussion Geomapping in Tableau Qlik view – Basics Google charts – Basics Dynamic charts with Google Docs Supplementary material & Case study discussion Closing session & Queries Web Analytics Introduction to Digital Media Analytics Introduction to Google Analytics Concept of Account, Property and View Concept of Sessions and Users Concept of Dimension, Metric and Segment Reading a Google Analytics Report Audience Analytics Acquisition Analytics Behaviour Analytics Real-Time Analytics Setting Up and Analysing Events Intelligent Events Setting Up and Analysing Experiments Setting Up and Measuring Conversion Goals Attribution Modelling Segment Reporting Designing Custom Reports Introduction to Google Adwords Search Marketing Display Marketing Google Adwords Analytics Managing a Google Analytics Account RDBMS with SQL and DWH Introduction to DBMS / RDBMS Data Modelling Physical Data Model Getting Started with SQL Lite DDL DML Introduction to Data Warehousing Dimensional Modelling Advanced SQL Olap Cubes Olap Cubes Practicals Artificial Intelligence & Deep Learning - Industry Practices This program is brought to you by Praxis B schoolCompanies both large and small are scrambling to hire qualified individuals with a plethora of data literacy skills. This makes now the perfect time for the candidates to take advantage of rewarding career opportunities in developing technical solutions, analyzing & documenting requirements, managing and communication, devising solutions and blending business with technology. This program also comes with the benefit of Placement support from 361 Degree Minds though you would not have the need since opportunities galore when you do this program.
By: 361 Degree Minds Consulting Pvt Ltd
This Post Graduate Program in Data Science and Data Visualization – designed by veterans in the Analytics industry; helps to establish a decent career in the growing Data and Analytics domain. This uniquely blended Program is brought to you by Praxis, a Top-ranked Analytics B-School in India. Post Graduate Program in Data Engineering – Visualization is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 12-15 months of faculty led Online mode. The following are the modules covered" Big Data 101 Big Data Characteristics Big Data and Business Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms Clustering Algorithms – UPGMA, single Link Clustering KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding Mathematics Modelling Introduction to key mathematical concepts Application of eigenvalues and eigenvectors Application of the graph Laplacian Application of PCA and SVD Coding in DB Environment Making Data Sets Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I Measures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Hadoop Introduction to Big Data and Hadoop Introduction to DBMS systems using MySQL Big Data and Hadoop EcoSystem HDFS Unix & HDFS Hands-on Map-Reduce basics Map Reduce Advanced Topics and Hands on Pig introduction and Hands on Pig Scripting Hive Introduction, Metastore, Limitations of Hive Comparison with Traditional Database and HIVE scripting Hive Data Types, Partitioning and Bucketing Hive Tables (Managed and External) Hive Continued Scoop Introduction and Hands-on Introduction to NoSql and HBASE HBASE architecture and Hands-on Access Methods Big Data with Spark and Python Python Understanding Basics of Python Control Structures and for loop Playing with while loop | break and continue Strings and files List Dictionary and Tuples Data Visualization with Tableau Need for visualizing data Research methodologies Importance of Big data visualization Tableau product offerings Installation of Tableau Public Working with Tableau - Live Case study/Discussion Creating interactive dashboards with Tableau Public Case study discussion Story Boarding with Tableau Public Case study discussion Geomapping in Tableau Qlik view – Basics Google charts – Basics Dynamic charts with Google Docs Supplementary material & Case study discussion Closing session & Queries RDBMS with SQL and DWH Introduction to DBMS / RDBMS Data Modelling Physical Data Model Getting Started with SQL Lite DDL DML Introduction to Data Warehousing Dimensional Modelling Advanced SQL Olap Cubes Olap Cubes Practicals Artificial Intelligence & Deep Learning - Industry Practices
This program is brought to you by Praxis B schoolData visualization post graduate program provides candidates a powerful way to communicate data-driven findings, motivate analyses, and detect flaws in their career phase in Engineering, Business Intelligent Analysis and Data Analysis. This program also comes with the benefit of Placement support from 361 Degree Minds though you would not have the need since opportunities galore when you do this program.
By: 361 Degree Minds Consulting Pvt Ltd
This Post Graduate Program in Data Science and Machine Learning has a perfect blend of Technology, Data Science and Business cases and insights; it stands out to be among the best in the world. It is imperative that career seekers grab this opportunity.This uniquely blended Program is brought to you by Praxis, a Top-ranked Analytics B-School in India. Post Graduate Program in Data Science is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity.Learners are required to complete 12-15 months of faculty led Online mode. The following are the modules covered" Big Data 101 Big Data Characteristics Big Data and Business Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms Clustering Algorithms – UPGMA, single Link Clustering KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding Mathematics Modelling Introduction to key mathematical concepts Application of eigenvalues and eigenvectors Application of the graph Laplacian Application of PCA and SVD Coding in DB Environment Making Data Sets Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I Measures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Hadoop Introduction to Big Data and Hadoop Introduction to DBMS systems using MySQL Big Data and Hadoop EcoSystem HDFS Unix & HDFS Hands-on Map-Reduce basics Map Reduce Advanced Topics and Hands on Pig introduction and Hands on Pig Scripting Hive Introduction, Metastore, Limitations of Hive Comparison with Traditional Database and HIVE scripting Hive Data Types, Partitioning and Bucketing Hive Tables (Managed and External) Hive Continued Scoop Introduction and Hands-on Introduction to NoSql and HBASE HBASE architecture and Hands-on Access Methods Big Data with Spark and Python Python Understanding Basics of Python Control Structures and for loop Playing with while loop | break and continue Strings and files List Dictionary and Tuples Data Mining 1 - Machine Learning with R & Python Introduction to NumPy Introduction to Pandas Slicing Data Exploratory Data Analysis Exploratory Data Analysis (Continue) Missing Value Imputation and Outlier Analysis Linear Regression Motivation Linear Regression optimization objective Linear Regression in Python Introduction to Regression Tree Introduction to Classification Tree Measures of Selecting the best Split Cluster Analysis – Hierarchical Clustering & k-Means Clustering Customer segmentation in Telecom Industry using Cluster Analysis k-Means clustering Association Rules mining Market Basket Analysis Data Mining 2 - Advanced Machine Learning with R & Python Sources of Error (Irreducible error, bias and variance) Formally defining the 3 Sources of Error Linear Regression – Multicollinearity (VIF) Qualitative Predictors – Use of Dummy Variables Observing overfitting in Polynomial Regression Regularized Regression (L2 – Regularization) – To avoid overfitting Regularized Regression (L1 – Regularization) – Feature selection using regularization Regularized Regression – How does regularized regression handles multicollinearity? Decision Tree – Pruning Bagging Models Designing your own Bagged Model Random Forest Boosting (Ada Boost) K Nearest Neighbour – Concept. kNN algorithm for k=1 and k>1 Writing a K Nearest Neighbour algorithm from scratch Comparison of kNN with Linear Regression; Difference between kNN and kMeans. Revision of basics of Linear Algebra The Theory of dimension reduction Practical – Compressing an image file [Practical using R Software] Practical – Compressing an image file [Practical using R Software] (Continue) RDBMS with SQL and DWH Introduction to DBMS / RDBMS Data Modelling Physical Data Model Getting Started with SQL Lite DDL DML Introduction to Data Warehousing Dimensional Modelling Advanced SQL Olap Cubes Olap Cubes Practicals Artificial Intelligence & Deep Learning - Industry Practices
This program is brought to you by Praxis B schoolThe Program in Machine Learning is strategically designed to make the candidates competent authority in the enticing world of Machine Learning by introducing you to the fundamentals and dynamics of Machine Learning for coding, linear classification, research and development of algorithms and to predict to extract patterns. This program also comes with the benefit of Placement support from 361 Degree Minds though you would not have the need since opportunities galore when you do this program.
By: 361 Degree Minds Consulting Pvt Ltd
Post Graduate Program in Data Science is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 6-12 months of faculty led Online mode. The following are the modules covered" Big Data 101 Big Data Characteristics Big Data and Business Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms Clustering Algorithms – UPGMA, single Link Clustering KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding Mathematics Modelling Introduction to key mathematical concepts Application of eigenvalues and eigenvectors Application of the graph Laplacian Application of PCA and SVD Coding in DB Environment Making Data Sets Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I Measures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Hadoop Introduction to Big Data and Hadoop Introduction to DBMS systems using MySQL Big Data and Hadoop EcoSystem HDFS Unix & HDFS Hands-on Map-Reduce basics Map Reduce Advanced Topics and Hands on Pig introduction and Hands on Pig Scripting Hive Introduction, Metastore, Limitations of Hive Comparison with Traditional Database and HIVE scripting Hive Data Types, Partitioning and Bucketing Hive Tables (Managed and External) Hive Continued Scoop Introduction and Hands-on Introduction to NoSql and HBASE HBASE architecture and Hands-on Access Methods Big Data with Spark and Python Python Understanding Basics of Python Control Structures and for loop Playing with while loop | break and continue Strings and files List Dictionary and Tuples Data Mining 1 - Machine Learning with R & Python Introduction to NumPy Introduction to Pandas Slicing Data Exploratory Data Analysis Exploratory Data Analysis (Continue) Missing Value Imputation and Outlier Analysis Linear Regression Motivation Linear Regression optimization objective Linear Regression in Python Introduction to Regression Tree Introduction to Classification Tree Measures of Selecting the best Split Cluster Analysis – Hierarchical Clustering & k-Means Clustering Customer segmentation in Telecom Industry using Cluster Analysis k-Means clustering Association Rules mining Market Basket Analysis Data Mining 2 - Advanced Machine Learning with R & Python Sources of Error (Irreducible error, bias and variance) Formally defining the 3 Sources of Error Linear Regression – Multicollinearity (VIF) Qualitative Predictors – Use of Dummy Variables Observing overfitting in Polynomial Regression Regularized Regression (L2 – Regularization) – To avoid overfitting Regularized Regression (L1 – Regularization) – Feature selection using regularization Regularized Regression – How does regularized regression handles multicollinearity? Decision Tree – Pruning Bagging Models Designing your own Bagged Model Random Forest Boosting (Ada Boost) K Nearest Neighbour – Concept. kNN algorithm for k=1 and k>1 Writing a K Nearest Neighbour algorithm from scratch Comparison of kNN with Linear Regression; Difference between kNN and kMeans. Revision of basics of Linear Algebra The Theory of dimension reduction Practical – Compressing an image file [Practical using R Software] Practical – Compressing an image file [Practical using R Software] (Continue) RDBMS with SQL and DWH Introduction to DBMS / RDBMS Data Modelling Physical Data Model Getting Started with SQL Lite DDL DML Introduction to Data Warehousing Dimensional Modelling Advanced SQL Olap Cubes Olap Cubes Practicals Artificial Intelligence & Deep Learning - Industry Practices
This program is brought to you by Praxis B schoolThe Program in Machine Learning is strategically designed to make the candidates competent authority in the enticing world of Machine Learning by introducing you to the fundamentals and dynamics of Machine Learning for coding, linear classification, research and development of algorithms and to predict to extract patterns.
By: 361 Degree Minds Consulting Pvt Ltd
Advanced Certificate Program in Business Analytics is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3-6 months of faculty led Online mode. The following are the modules covered
This program is brought to you by Praxis B school
This advanced course is designed to provide in-depth knowledge of data handling and Business Analytics’ tools that can be used for fact-based decision-making. The candidates will be able to analyze and solve problems from different industries such as manufacturing, service, retail, software, banking and more.
By: 361 Degree Minds Consulting Pvt Ltd
Advanced Certificate Program in Data Visualization is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3-6 months of faculty led Online mode. The following are the modules covered
Data Visualization with D3
This program is brought to you by Praxis B school
The program is designed to expose candidates to rigorous market research, logistic coding, knowledge expertise in the field of data mining, statistical and problem-solving skills, data visualization and communication skills.
By: 361 Degree Minds Consulting Pvt Ltd
Advanced Certificate Program in Data Science is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3-6 weeks of faculty led Online mode. The following are the subjects covered
This program is brought to you by Praxis B school
The course will make the candidates expert in Machine Learning and data automation without explicit programming. The candidates will be mastered in Machine Learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer.
By: 361 Degree Minds Consulting Pvt Ltd
Professional Certificate Program in Machine Learning is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 20 weeks of faculty led Online mode. The following are the subjects covered
Big Data with Spark and Python
Artificial Intelligence & Deep Learning - Industry Practices
This program is brought to you by Praxis B school
The Professional Certificate Program in Machine Learning is mid-range program, strategically designed to make the candidates competent authority in the enticing world of Machine Learning by introducing you to the fundamentals and dynamics of Machine Learning for coding, linear classification, research and development of algorithms and to predict to extract patterns.
By: 361 Degree Minds Consulting Pvt Ltd
Certificate Program in Data Visualization is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3 months of faculty led Online mode. The following are the subjects covered
This program is brought to you by Praxis B school
By: 361 Degree Minds Consulting Pvt Ltd
Certificate program in business analytics is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3 months of faculty led Online mode. The following are the subjects covered
Companies both large and small are scrambling to hire qualified individuals with a plethora of data literacy skills. This makes now the perfect time for the candidates to take advantage of rewarding career opportunities in developing technical solutions, analyzing & documenting requirements, managing and communication, devising solutions and blending business with technology.
By: Simpliv Llc
About this Course
This course is for those who want to step into Data Science domain, specially into Machine Learning, though I will be covering everything in deep and from the scratch.
This course will take your knowledge in Python from A to Z in a day ( Ofcourse if you can sit in one go ).
I have covered everything from "Hello World" in Python to all the required "Libraries like pandas and numpy"
Basic knowledge
No prior knowledge or prerequisites as everything will be taught from the scratch.
What you will learn
Everything in Python that is required for Data Science, specially with Machine Learning/Deep Learning Domain.
By: Simpliv Llc
About this Course
On the off chance that you are going for a profession as a Data Scientist or Business Analyst at that point looking over your statistics abilities is something you have to do.
In any case, it's only difficult to begin... Learning/re-adapting ALL of details just appears like an overwhelming undertaking.
That is precisely why we have made this course!
Here you will rapidly get the significant details learning for a Data Scientist or Analyst.
This isn't simply one more exhausting course on details.
This course is exceptionally pragmatic.
I have particularly included true models of business difficulties to demonstrate to you how you could apply this learning to help YOUR vocation.
In the meantime you will ace points, for example, dispersions, the z-test, the Central Limit Theorem, theory testing, certainty interims, measurable criticalness and some more!
So what are you sitting tight for?
Select now and enable your profession!
Basic knowledge
What you will learn
By: Rcmt Dubai
The program provides access to high-quality learning content, simulation exams, a community moderated by experts, and other resources that ensure you follow the optimal path to your dream role of data scientist. With this course You will be able to do following independently: 1. Fundamental R and Python programming skills 2. Statistical concepts such as probability, inference, and modeling and how to apply them in practice 3. Gain experience with Numpy, Pandas and scikit library, including data visualization with ggplot2 and data wrangling with dplyr 4. Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and Jupyter 5. Implement machine learning algorithms 6. In-depth knowledge of fundamental data science concepts through motivating real-world case studies Rolla’s Data Science Program will help you master skills and tools like Statistics, Hypothesis testing, Data analysis, Data wrangling, Data Visualization, Classification models, Regression models, Hadoop, Spark, PROC SQL, SAS Macros. These skills will help you prepare for the role of a Data Scientist.
By: Innosoft Gulf
We offer the following Data Science courses:
By: Zekelabs
This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material. Fundamentals of machine learning will be taught here & projects will be done using it.
Visual communication is effective only when it is aligned with the way people see and think. The course provides insights on the importance of data visualization, fundamental principles, as well as means to increase non-verbal communication skills through effective visualizations.
This course will help you improve communication within your company, through visual displays of quantitative data.
This course aims to improve the decision-making process through a rigorous data analysis within the company, as well as to enable managers and analysts to draw insights from both quantitative and qualitative data. Participants will understand, through practical learning, how to effectively collect, analyze and interpret data for a better decision making process, based on historical data and trend analysis.
Intensive learning program on MCSE Data Platform is available here for all interested pupil. Our course module is excessively practicals oriented. Technical training we provide, is always based on the recent professional requirement. Professional faculties take classes. Unique tutoring methodologies are followed by our highly skilled teachers.
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