Data science
Course Description
Data Science Certification from SGIT, Steinbeis University, Germany:
Accelerate your career with Data Science certification from SGIT, Steinbeis University Germany , one of the leading universities in Germany. This course is a perfect blend of theory, case studies and capstone projects. The course curriculum has been designed by Steinbeis University and considered to be the best in the industry. Get noticed by recruiters across the globe with the international certification. Post certification one will gain the alumnus status in Steinbeis University.
What is the certification process?
Post completion of the training, one should take an online examination facilitated by the university and should attain 60% or more to complete the course and gain the certification. Subsequently participants can check their alumnus status on SGIT , Steinbeis Global Institute Tübingen.
Data Science Certification Course Training In Abu Dhabi, United Arab Emirates (UAE)
Okstech offers an interactive instructor-led 160 hours of virtual online Data Science certification course training in Abu Dhabi, the most comprehensive Data Science course in the market, covering the complete Data Science life cycle concepts from Data Extraction, Data Cleansing, Data Integration, Data Mining, building Prediction models and Data Visualization. Skills and tools ranging from Statistical Analysis, Text mining, Regression models, Natural Language Processing (NLP), Hypothesis testing, Predictive Analytics, Machine Learning, R Studio, Tableau, programming languages like R, Python for Data Science are covered extensively as part of this 160 hours of Data Science training. Participants will be provided with an opportunity to work on 60+ assignments and one capstone project which ensures the hands-on experience for the participants. Okstech is considered as the leader in the space of Data Science training in Abu Dhabi, United Arab Emirates (UAE).
Data Mining
Data Mining is unveiling the underlying patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision-making changed the companies, the way they operate the business and improved revenues significantly Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principal Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Data Mining concepts will be extensively covered as part of our Data Science certification course training.
Python For Data Science
Learn about the installation of Python using various distributions, python operators, string handling, various data types, lists, tuple, string, dictionary, conditional statements, functions, loops, modules, packages. Also learn about file handling, exception handling, regular expressions and data analytics. Learn about exploratory data analysis and data visualization libraries such as NumPy, Pandas, Matplotlib, Seaborn. Data Science concepts are extremely pivotal and hence participants will learn about Linear regression, Logistic regression, Multinomial regression, KNN, Naive Bayes, Decision Tree, Random Forest, Ensemble techniques and black box techniques such as Support Vector Machine and Neural Network. Lastly, data optimization techniques such as Gradient Descent, etc.
R For Data Science
As part of the Data Science certification course, R programming and R Studio will be extensively covered. Learn about the basics of R for Data Science, ranging from reading all the wide variety of files such as SAS, SPASS, Minitab, Pdf, Excel, CSV, Text, etc. Understanding various mandatory packages, connecting to ODBC. Learn about vectors, lists, matrices, data frames, inbuild functions, combining datasets using cbind, rbind, merge, etc. Data Manipulation techniques such as grep, grepl, sub, gsub, regexpr, gregexpr, apply, lapply, sapply, tapply, etc., will be explained in finer details. Data Exploration techniques such as summarize, aggregate, Hmisc package, describe a function, will be explained using detailed real-world case studies. Learn about Data Visualization techniques plot, line plot, scatter plot, box plot, scatter plot, star plot, stem and leaf plot, pie chart, histogram, rug plot, sunflower plot, hexbin plot, tableplot, mosaic plot, RColorBrewer package, etc.
What Is Instructor-Led Online Data Science Training?
Instructor-Led online training is an interactive mode of training where participants and trainer will log in at the same time and live sessions will be done virtually. These sessions will provide scope for active interaction between you and the trainer.
What Is Data Science? Who Is Data Scientist?
Data Science is all about mining hidden insights of data pertaining to trends, behaviour, interpretation and inferences to enable informed decisions to support the business. The professionals who perform these activities are said to be a Data Scientist / Science professional. Data Science is the most high-in-demand profession and as per Harvard and the most sort after profession in the world.
Why You Should Take The Data Science Course?
Is Data Science Certification Being Worth Pursuing As A Career?
The answer is a big YES for myriad reasons. Digitalization across the domains is creating tons of data and the demand for the Data Science professionals who can evaluate and extract meaningful insights is increasing and creating millions of jobs in the space of Data Science. There is a huge void between the demand and supply and thereby creating ample job opportunities and salaries. Data Scientists are considered to be the highest in the job market. Data Scientist career path is long-lasting and rewarding as the data generation is increasing by leaps and bounds and the need for the Data Science professionals will increase perpetually.
- 1.4 Lakh jobs are vacant in Data Science, Artificial Intelligence and Big Data roles according to NASSCOM
- The world will notice a deficit of 2.3 Lakh Data Science professionals by 2021
- The Demand for Data Scientist professionals has increased by 417% in the year 2018, in India, as per the Talent Supply Index
- Data Science is the best job to pursue according to Glassdoor 2018 rankings
- Harvard Business Review stated that ‘Data Scientist is the sexiest job of the 21st century’
You May Question If Data Science Certification Is Worth It?
The answer is yes. Data Science / Analytics creating myriad jobs in all the domains across the globe. Business organizations realised the value of analysing the historical data in order to make informed decisions and improve their business. Digitalization in all the walks of the business is helping them to generate the data and enabling the analysis of the data. This is helping to create myriad data science/analytics job opportunities in this space. The void between the demand and supply for the Data Scientists is huge and hence the salaries pertaining to Data Science are sky high and considered to be the best in the industry. Data Scientist career path is long and lucrative as the generation of online data is perpetual and growing in the future.
Who Should Do The Data Science Course?
Professionals who can consider Data Science course as a next logical move to enhance in their careers include:
- Professional from any domain who has logical, mathematical and analytical skills
- Professionals working on Business intelligence, Data Warehousing and reporting tools
- Statisticians, Economists, Mathematicians
- Software programmers
- Business analysts
- Six Sigma consultants
- Fresher from any stream with good Analytical and logical skills
Course Curriculum
Module 1 – Data Science Project Lifecycle
Module 2 – Introduction To Basic Statistics Using R And Python
Module 3 – Probability And Hypothesis Testing
Module 4 -Exploratory Data Analysis -1
Module 5 – Linear Regression
Module 6 – Logistic Regression
Module – 7 Deployment
Module 8 – Data Mining Unsupervised Clustering
Module 9 – Dimension Reduction Techniques
Module 10 – Association Rules
Module 11 – Recommender System
Module 12 – Introduction To Supervised Machine Learning
Module 13 – Decision Tree
Module 14 – Exploratory Data Analysis – 2
Module 15: Feature Engineering
Module 16: Model Validation Methods
Module 17:Ensembled Techniques
Module 18 – KNN And Support Vector Machines
Module 19 – Regularization Techniques
Module 20 – Neural Networks
Module 21 – Text Mining
Module 22 – Natural Language Processing
Module 23 – Naive Bayes
Module 24 – Forecasting
Module 25 – Survival Analysis
Module 26 – End To End Project Description With Deployment
Assignments/Projects/Placement Support
Module 27 – Assignments
Module 28 – Projects
Module 29 – Resume Prep And Interview Support
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