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 discipline that involves extracting valuable insights and knowledge from large volumes of structured and unstructured data. It utilizes various techniques, algorithms, and systems to analyze, interpret, and present data.
The Data Science process functions through collecting, cleaning, and analyzing data to derive meaningful patterns and trends. It often employs statistical models, machine learning algorithms, and data visualization techniques to make informed decisions.
Practical applications of Data Science include predictive analytics, fraud detection, recommendation systems, sentiment analysis, and optimizing business processes across various industries.
Key components of a Data Science pipeline include data collection, data cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment.
Common programming languages in Data Science include Python and R, renowned for their extensive libraries and frameworks facilitating data manipulation, analysis, and machine learning.
Machine learning is integral to Data Science, empowering systems to learn patterns from data and make predictions or decisions without explicit programming. It enhances the ability to extract valuable insights from complex datasets.
Big Data is closely tied to Data Science, involving the handling and analysis of massive datasets that traditional tools may struggle with. Data Science techniques and algorithms are often applied to extract meaningful information from Big Data.
Data Science finds applications in industries such as healthcare, finance, marketing, and manufacturing to optimize operations, improve decision-making, and enhance overall business performance.
While Data Science encompasses a broader range of activities, including data cleaning, exploration, and visualization, machine learning specifically focuses on developing algorithms that enable systems to learn patterns and make predictions.
Individuals from diverse backgrounds, including IT professionals, statisticians, analysts, and business professionals, are eligible to pursue Data Science certification courses. A basic understanding of statistics and programming is beneficial for learning Data Science.
The data science job market in Zagreb is on the rise in 2024, witnessing increased demand for skilled professionals.
Data science internships hold value in Zagreb, providing practical experience and enhancing one's employability.
the data scientist's salary in Zagreb ranges from HRK 27,000 per month according to a Glassdoor report.
Yes, individuals without prior experience can enroll in a data science course and secure a job in Zagreb, as companies are willing to hire skilled beginners.
A postgraduate degree is not obligatory for enrolling in data science training courses in Zagreb; many programs accept candidates with relevant undergraduate backgrounds.
Businesses in Zagreb harness data science for growth by improving decision-making, optimizing operations, and enhancing overall customer experiences.
In finance, data science is applied to risk management, fraud detection, and predictive analytics.
Data science contributes to e-commerce by powering recommendation systems, personalized marketing, and accurate demand forecasting.
In the realm of cybersecurity, data science plays a crucial role in detecting anomalies, identifying patterns, and enhancing overall threat detection and prevention measures.
In manufacturing and supply chain management, data science is instrumental in optimizing production processes, predicting demand, and improving overall logistics efficiency.
The Datamites™ Certified Data Scientist course covers programming, statistics, machine learning, and business knowledge. Emphasizing Python as the primary language, with the inclusion of R for those familiar, the course provides a robust foundation in data science. Completion results in an IABAC™ certificate, preparing individuals for success as proficient data science professionals.
While a statistical background can be beneficial, it's not always a prerequisite for a data science career in Zagreb. Proficiency in relevant tools, programming languages, and practical problem-solving skills often take precedence.
DataMites offers a variety of certifications in Zagreb, including Diploma in Data Science, Certified Data Scientist, Data Science for Managers, Data Science Associate, Statistics for Data Science, Python for Data Science, and specialized courses in Operations, Marketing, HR, Finance, among others.
For beginners in Zagreb, options include courses like Certified Data Scientist, Data Science Foundation, and Diploma in Data Science to establish foundational knowledge.
In Zagreb, DataMites provides specialized courses for professionals, covering Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and certifications in Operations, Marketing, HR, and Finance.
The data science course in Zagreb offered by DataMites has a duration of 8 months.
Career mentoring sessions at DataMites are interactive, offering personalized guidance on resume building, interview preparation, and career strategies. Participants gain valuable insights and tactics to enhance their professional journey in data science.
Upon successful completion, participants receive the prestigious IABAC Certification from DataMites. This globally recognized certification validates their proficiency in data science concepts and applications, enhancing credibility in the field.
To excel in data science, a solid foundation in mathematics, statistics, and programming is crucial. Develop strong analytical skills, proficiency in Python or R, and hands-on experience with extensive datasets and tools like Hadoop or SQL databases.
Advantages include adaptability for self-paced learning, accessibility regardless of location, a comprehensive curriculum aligned with industry needs, industry-relevant material, guidance from skilled instructors, and engaging learning through interactive features.
The fee for data science training in Zagreb with DataMites ranges from HRK 3,311 to HRK 9,219.
Certainly, DataMites offers a comprehensive Data Scientist Course in Zagreb that includes hands-on learning with over 10 capstone projects, including a dedicated client/live project for real-world application and industry exposure.
Instructors at DataMites are chosen based on certifications, extensive industry experience, and demonstrated mastery of the subject matter.
DataMites provides flexible learning options, including Live Online sessions and self-study, catering to individual preferences.
With the FLEXI-PASS option in DataMites' Certified Data Scientist Course, participants can join multiple batches for a comprehensive learning experience, revisiting topics, clarifying doubts, and enhancing their understanding across various sessions.
Yes, DataMites issues a Certificate of Completion for the Data Science Course in Zagreb, validating participants' proficiency in data science.
Participants must bring a valid Photo ID Proof, such as a National ID card or Driving License, to obtain a Participation Certificate and schedule the certification exam as necessary.
If participants miss a session in the DataMites Certified Data Scientist Course in Zagreb, they can access recorded sessions or participate in support sessions to catch up on missed content and address doubts.
Certainly, prospective participants at DataMites can attend a demo class before enrolling in the Certified Data Scientist Course in Zagreb to assess teaching style, course content, and overall structure.
DataMites integrates internships into its certified data scientist course in Zagreb, providing a unique learning experience that combines theoretical knowledge with practical industry exposure.
Upon completing the Data Science training, participants receive an internationally recognized IABAC® certification, validating their expertise and enhancing 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.