Instructor Led Live Online
Self Learning + Live Mentoring
Customize Your Training
The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
MODULE 1: DATA SCIENCE COURSE INTRODUCTION
MODULE 2: DATA SCIENCE ESSENTIALS
MODULE 3: DATA SCIENCE DEMO
MODULE 4: ANALYTICS CLASSIFICATION
MODULE 5: DATA SCIENCE AND RELATED FIELDS
MODULE 6: DATA SCIENCE ROLES & WORKFLOW
MODULE 7: MACHINE LEARNING INTRODUCTION
MODULE 8: DATA SCIENCE INDUSTRY APPLICATIONS
MODULE 1: PYTHON BASICS
MODULE 2: PYTHON CONTROL STATEMENTS
MODULE 3: PYTHON DATA STRUCTURES
MODULE 4: PYTHON FUNCTIONS
MODULE 5: PYTHON NUMPY PACKAGE
MODULE 6: PYTHON PANDASPACKAGE
MODULE 1: OVERVIEW OF STATISTICS
MODULE 2: HARNESSING DATA
MODULE 3: EXPLORATORY DATA ANALYSIS
MODULE 4: HYPOTHESIS TESTING
MODULE 5: CORRELATION AND REGRESSION
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: PYTHON NUMPY & PANDAS PACKAGE
MODULE 3: VISUALIZATION WITH PYTHON
MODULE 4: ML ALGO: LINEAR REGRESSION
MODULE 5: ML ALGO: KNN
MODULE 6: ML ALGO: LOGISTIC REGRESSION
MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 8: ML ALGO: K MEANS CLUSTERING
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: ML ALGO: LINEAR REGRESSSION
MODULE 3: ML ALGO: LOGISTIC REGRESSION
MODULE 4: ML ALGO: KNN
MODULE 5: ML ALGO: K MEANS CLUSTERING
MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 7: ML ALGO: DECISION TREE
MODULE 8 : ML ALGO: NAÏVE BAYES
MODULE 9: GRADIENT BOOSTING, XGBOOST
MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN)
MODULE 12: ADVANCED ML CONCEPTS
MODULE 1: TIME SERIES FORECASTING - ARIMA
MODULE 2: FEATURE ENGINEERING
MODULE 3: SENTIMENT ANALYSIS
MODULE 4: REGULAR EXPRESSIONS WITH PYTHON
MODULE 5: ML MODEL DEPLOYMENT WITH FLASK
MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL
MODULE 7: AWS CLOUD FOR DATA SCIENCE
MODULE 8: AZURE FOR DATA SCIENCE
MODULE 1: DATABASE INTRODUCTION
MODULE 2: SQL BASICS
MODULE 3: DATA TYPES AND CONSTRAINTS
MODULE 4: DATABASES AND TABLES (MySQL)
MODULE 5: SQL JOINS
MODULE 6: SQL COMMANDS AND CLAUSES
MODULE 7 : DOCUMENT DB/NO-SQL DB
MODULE 1: GIT INTRODUCTION
MODULE 2: GIT REPOSITORY and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
MODULE 4: TAGGING, BRANCHING AND MERGING
MODULE 5: UNDOING CHANGES
MODULE 6: GIT WITH GITHUB AND BITBUCKET
MODULE 1: BIG DATA INTRODUCTION
MODULE 2 : HDFS AND MAP REDUCE
MODULE 3: PYSPARK FOUNDATION
MODULE 4: SPARK SQL and HADOOP HIVE
MODULE 5 : MACHINE LEARNING WITH SPARK ML
MODULE 6: KAFKA and Spark
MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION
MODULE 2: BI WITH TABLEAU: INTRODUCTION
MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE
MODULE 4: TABLEAU : BUSINESS INSIGHTS
MODULE 5: DASHBOARDS, STORIES AND PAGES
MODULE 6: BI WITH POWER-BI
Data Science is the specialized discipline dedicated to extracting valuable insights and knowledge from extensive sets of both structured and unstructured data. It involves employing various techniques, algorithms, and systems to analyze, interpret, and present data meaningfully.
The process of Data Science involves a systematic approach to data collection, cleaning, and analysis to unveil meaningful patterns and trends. Through the utilization of statistical models, machine learning algorithms, and data visualization techniques, decisions are made based on the discovered insights.
Data Science exhibits practical applications in predictive analytics, fraud detection, recommendation systems, sentiment analysis, and business process optimization across diverse industries, showcasing its adaptability and significance.
Crucial elements of a Data Science pipeline encompass data collection, cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment. These stages collectively contribute to the comprehensive process of deriving insights from data.
Frequently used programming languages in Data Science include Python and R, chosen for their popularity and the availability of extensive libraries and frameworks facilitating data manipulation, analysis, and the implementation of machine learning algorithms.
Machine learning is pivotal in Data Science, enabling systems to autonomously discern patterns from data, make predictions, and enhance the capacity to extract valuable insights from complex datasets without explicit programming.
The relationship between Big Data and Data Science is close-knit, as Data Science involves handling and analyzing extensive datasets that conventional tools may struggle to manage. Data Science methodologies and algorithms are frequently applied to extract meaningful information from the vast expanse of Big Data.
Data Science finds practical application in sectors such as healthcare, finance, marketing, and manufacturing, optimizing operations, refining decision-making processes, and enhancing overall business performance.
While Data Science encompasses a broader spectrum of activities, including data cleaning, exploration, and visualization, machine learning specifically focuses on crafting algorithms that enable systems to learn patterns and autonomously make predictions.
Eligible individuals for Data Science certification courses come from diverse backgrounds, including IT professionals, statisticians, analysts, and business experts. A foundational understanding of statistics and programming proves beneficial for those venturing into the field of Data Science.
As of 2024, the data science job market in Hungary is undergoing significant expansion, witnessing a surge in demand for skilled professionals.
A prominent choice for comprehensive data science training in Hungary is the Certified Data Scientist Course, covering vital areas like machine learning and data analysis.
In Hungary, data science internships hold substantial importance, offering hands-on experience that greatly enhances one's employability in the flourishing field.
Indeed, entry-level individuals can enroll in data science courses and successfully secure jobs in Hungary, as companies actively seek skilled newcomers.
No, a postgraduate degree is not mandatory for joining data science training courses in Hungary; many programs welcome candidates with relevant undergraduate backgrounds.
Businesses in Hungary harness data science to fuel growth by improving decision-making processes, streamlining operations, and enhancing overall customer experiences.
In Hungary's financial sector, data science finds application in areas such as risk management, fraud detection, and predictive analytics, significantly boosting industry efficiency.
In Hungary, data science is a linchpin in e-commerce, steering recommendation systems, personalized marketing, and accurate demand forecasting, thereby elevating the overall customer experience.
In Hungary's cybersecurity landscape, data science plays a critical role in detecting anomalies, recognizing patterns, and strengthening threat detection and prevention measures.
In the realms of manufacturing and supply chain management in Hungary, data science serves as a key instrument in optimizing production processes, predicting demand, and refining logistics efficiency to enhance overall operational performance.
The salary of a data scientist in Hungary ranges from HUF 7,494,983 per year according to a Glassdoor report.
The Datamites™ Certified Data Scientist course delves into essential facets of data science, encompassing programming, statistics, machine learning, and business acumen. The program places a particular emphasis on Python as the primary programming language, with provision for those familiar with R. Completion of the course, coupled with the IABAC™ certificate, empowers individuals to tackle real-world data science challenges.
While beneficial, a statistical background is not always obligatory for initiating a data science career in Hungary. Emphasis is often placed on proficiency in relevant tools, programming languages, and practical problem-solving skills.
In Hungary, DataMites provides a diverse array of data science certifications, including a Diploma in Data Science, Certified Data Scientist, Data Science for Managers, Data Science Associate, Statistics for Data Science, Python for Data Science, and specialized certifications in Marketing, Operations, Finance, and HR.
For beginners in Hungary, foundational courses like Certified Data Scientist, Data Science Foundation, and Diploma in Data Science provide essential training in data science.
DataMites in Hungary caters to working professionals with courses such as Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and specialized certifications in Operations, Marketing, HR, and Finance.
The data science course in Hungary offered by DataMites spans 8 months.
Career mentoring sessions at DataMites are personalized and interactive, offering tailored guidance on resume development, interview preparation, and effective career strategies. These sessions aim to provide participants with valuable insights to enrich their professional journey in data science.
Upon successful completion of the training, participants receive the prestigious IABAC Certification from DataMites, widely recognized internationally. This certification validates proficiency in data science principles and practical applications.
To excel in data science, a solid foundation in mathematics, statistics, and programming is crucial. It is recommended to possess analytical skills, proficiency in languages like Python or R, and hands-on experience with tools like Hadoop or SQL databases.
Opting for online data science training in Hungary provides advantages such as flexibility, accessibility, a comprehensive curriculum aligned with industry needs, industry-relevant content, experienced instructors, interactive learning experiences, and the freedom to learn at one's own pace.
The pricing for DataMites' data science training in Hungary varies between HUF 188,707 and HUF 471,823, depending on the specific program chosen.
DataMites' Data Scientist Course in Hungary is comprehensive, featuring hands-on learning with over 10 capstone projects, including a dedicated client/live project. This ensures participants gain practical experience and can apply their acquired skills in real-world scenarios.
Instructors at DataMites are selected based on their certifications, extensive industry experience, and expertise in the subject matter. This guarantees participants receive high-quality instruction from seasoned professionals.
DataMites offers flexible learning methods, including Live Online sessions and self-study options, catering to the diverse preferences of participants.
The Flexi-Pass feature in DataMites' Certified Data Scientist Course allows participants to attend multiple batches, providing flexibility to revisit topics, address queries, and reinforce understanding across various sessions for a comprehensive grasp of the course content.
Certainly, upon completing the DataMites' Data Science Course, participants have the option to request a Certificate of Completion through the online portal. This certification serves as a testament to their data science proficiency, enhancing their competitiveness in the job market.
Yes, participants are required to bring a valid Photo ID Proof, such as a National ID card or Driving License, to secure a Participation Certificate and facilitate the scheduling of the certification exam as needed.
In case of a missed session during the DataMites Certified Data Scientist Course in Hungary, participants typically have the option to access recorded sessions or attend support sessions to make up for any missed content and address queries.
Prospective participants at DataMites are encouraged to attend a demo class before making any payments for the Certified Data Scientist Course in Hungary. This allows them to assess the teaching style, course content, and overall structure before committing.
Certainly, DataMites integrates internships into its certified data scientist course in Hungary, offering a unique learning experience that combines theoretical knowledge with practical industry exposure. This approach enhances skills and opens up job opportunities in the dynamic field of data science.
Upon successful completion of the Data Science training, participants will be awarded an internationally recognized IABAC® certification. This certification validates their expertise in the field, enhancing their employability on a global scale.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.