Instructor Led Live Online
Self Learning + Live Mentoring
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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 dedicated practice of extracting valuable insights and knowledge from extensive sets of both structured and unstructured data, employing various techniques, algorithms, and systems to analyze, interpret, and present data meaningfully.
The process of Data Science involves systematic data collection, cleaning, and analysis to uncover meaningful patterns and trends. Utilizing statistical models, machine learning algorithms, and data visualization techniques, decisions are made based on the findings.
Data Science has practical applications in predictive analytics, fraud detection, recommendation systems, sentiment analysis, and business process optimization across various industries, showcasing its versatility and significance.
Vital components of a Data Science pipeline include data collection, data cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment. These stages contribute to the comprehensive process of deriving insights from data.
Python and R are commonly used programming languages in Data Science due to their popularity and the availability of extensive libraries and frameworks facilitating data manipulation, analysis, and implementation of machine learning algorithms.
Machine learning is crucial in Data Science as it empowers systems to discern patterns from data autonomously, enabling predictions and decisions without explicit programming and enhancing the capacity to extract valuable insights from intricate datasets.
The connection between Big Data and Data Science is intimate, as Data Science involves handling and analyzing extensive datasets that conventional tools might struggle to manage. Data Science methodologies and algorithms are often employed 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 concentrates on crafting algorithms that enable systems to learn patterns and make predictions autonomously.
Eligible individuals for Data Science certification courses come from varied backgrounds, including IT professionals, statisticians, analysts, and business experts. A foundational understanding of statistics and programming proves advantageous for those entering the realm of Data Science.
In 2024, the data science job market in Budapest is experiencing notable growth with an increasing demand for skilled professionals.
The Certified Data Scientist Course in Budapest is a leading choice for individuals seeking comprehensive data science training, covering essential areas such as machine learning and data analysis.
In Budapest, data science internships are highly significant, providing hands-on experience and significantly contributing to one's employability in the growing field.
Yes, individuals at the entry level can pursue a data science course and successfully secure jobs in Budapest, as companies actively seek skilled newcomers.
No, having a postgraduate degree is not mandatory for joining data science training courses in Budapest; many programs are open to candidates with relevant undergraduate backgrounds.
Businesses in Budapest use data science to drive growth by refining decision-making processes, streamlining operations, and enhancing overall customer experiences.
In the financial sector of Budapest, data science is applied in areas such as risk management, fraud detection, and predictive analytics, significantly contributing to industry efficiency.
In Budapest, data science is pivotal in e-commerce by driving recommendation systems, personalized marketing, and accurate demand forecasting, enhancing the overall customer experience.
In the realm of cybersecurity in Budapest, data science plays a crucial role in detecting anomalies, recognizing patterns, and fortifying threat detection and prevention measures.
In the domains of manufacturing and supply chain management in Budapest, data science is instrumental in optimizing production processes, predicting demand, and refining logistics efficiency for enhanced operational performance.
The salary of a data scientist in Budapest ranges from HUF 12,00,000 per year according to a Glassdoor report.
The Datamites™ Certified Data Scientist course encompasses crucial aspects of data science, including programming, statistics, machine learning, and business knowledge. The curriculum emphasizes Python as the primary programming language, while also accommodating professionals familiar with R. Completion of the course, coupled with the IABAC™ certificate, equips individuals to tackle real-world data science challenges.
While advantageous, a statistical background is not always mandatory for starting a data science career in Budapest. The focus is often on proficiency in relevant tools, programming languages, and practical problem-solving skills.
In Budapest, DataMites provides a diverse range 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 Budapest, introductory courses such as Certified Data Scientist, Data Science Foundation, and Diploma in Data Science offer foundational training in data science.
DataMites in Budapest caters to working professionals with courses like 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 Budapest offered by DataMites spans for 8 months.
Career mentoring sessions at DataMites are personalized and engaging, providing tailored guidance on resume development, interview readiness, and effective career strategies. These sessions aim to offer participants valuable insights to enrich their professional journey in data science.
Upon successful completion of the training, participants receive the esteemed IABAC Certification from DataMites. Widely recognized internationally, this certification validates one's proficiency in data science principles and practical applications.
To succeed in data science, a strong background in mathematics, statistics, and programming is essential. 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 Budapest offers benefits 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 DataMites' data science training fees in Budapest ranges from HUF 188,707 to HUF 471,823 depending on the specific program selected.
Indeed, DataMites provides a comprehensive Data Scientist Course in Budapest that includes hands-on learning with over 10 capstone projects and a dedicated client/live project. This practical approach ensures participants gain real-world experience and apply their acquired skills.
Trainers at DataMites are chosen based on their certifications, extensive industry experience, and expertise in the subject matter. This ensures that 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 the 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 the event of a missed session during the DataMites Certified Data Scientist Course in Budapest, participants typically have the option to access recorded sessions or attend support sessions to make up for any missed content and address any queries.
Potential participants at DataMites are encouraged to attend a demo class before making any payments for the Certified Data Scientist Course in Budapest. This allows them to evaluate the teaching style, course content, and overall structure before committing.
Certainly, DataMites integrates internships into its certified data scientist course in Budapest, 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.