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 a multidisciplinary field that employs scientific methods to extract insights from structured and unstructured data, encompassing processes, algorithms, and systems.
The Data Science process involves collecting, cleaning, and analyzing data using statistical techniques and machine learning algorithms, followed by presenting the findings to support decision-making.
Data Science is applicable in diverse domains such as finance, healthcare, marketing, and social media, supporting tasks like predictive modeling and pattern recognition.
Key stages in a Data Science pipeline include data collection, cleaning, exploratory data analysis, feature engineering, modeling, evaluation, and deployment.
Big Data involves managing massive datasets, and Data Science utilizes Big Data technologies for efficient processing and analysis of large volumes of information.
Data Science enhances e-commerce by providing personalized recommendations, demand forecasting, and fraud detection, thereby optimizing user experiences and increasing business efficiency.
Data Science is crucial in cybersecurity by identifying patterns in network traffic, detecting anomalies, and predicting potential security threats, strengthening digital defences.
Industries like healthcare, finance, and manufacturing leverage Data Science for tasks such as patient diagnosis, risk management, and process optimization, showcasing its versatile applications.
While Data Science is a broader field involving data analysis, machine learning is a subset that specifically focuses on algorithms enabling computers to learn from data and make predictions.
Individuals with a background in mathematics, statistics, computer science, or related fields are typically qualified to pursue certification courses in Data Science.
Building an impactful data science portfolio involves showcasing projects on platforms like GitHub and highlighting skills such as coding, data analysis, and visualization.
Yes, individuals from non-coding backgrounds can transition to data science by learning programming languages like Python, focusing on statistics, and acquiring knowledge in machine learning.
A background in mathematics, statistics, computer science, or a related field is commonly sought for a career in data science.
Crucial skills for a Data Scientist include proficiency in programming languages (e.g., Python, R), statistical analysis, machine learning, data manipulation, and effective communication.
Start a data science career in Ireland by acquiring relevant skills, networking, and joining local data science communities.
The state of the data science job market in Ireland in 2024 depends on demand. Checking job portals and networks is advisable to assess the current situation.
The Certified Data Scientist Course in Ireland is widely recognized as an excellent option for data science training, covering essential topics such as machine learning and data analysis.
Data science internships in Ireland are valuable as they provide practical experience, help build a professional network, and enhance overall employability.
Data scientists in Ireland can anticipate a salary ranging from EUR 65,813 per month, according to a Glassdoor report.
Yes, individuals with no prior experience can pursue a data science course and secure a job in Ireland by building a strong portfolio and actively applying to entry-level positions.
The Datamites™ Certified Data Scientist course is an extensive program that includes programming, statistics, machine learning, and business knowledge. It focuses on Python as the primary language, with the optional inclusion of R. Completion of the course leads to an IABAC™ certificate, preparing individuals for proficient roles in data science.
While a statistical background can be beneficial, it is not always necessary for a data science career in Ireland. Proficiency in relevant tools, programming languages, and practical problem-solving skills are often prioritized.
DataMites in Ireland provides a variety of certifications, 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 Marketing, Operations, Finance, and HR.
Beginners in Ireland can explore foundational training options such as Certified Data Scientist, Data Science Foundation, and Diploma in Data Science.
Yes, DataMites in Ireland offers courses tailored for professionals, including Statistics for Data Science, Data Science with R Programming, Python for Data Science, and specialized certifications in Operations, Marketing, HR, and Finance.
The data science course in Ireland offered by DataMites has a duration of 8 months.
Career mentoring sessions at DataMites follow an interactive format, offering personalized guidance on resume building, interview preparation, and career strategies to enhance participants' professional journeys in data science.
Upon completion, participants receive the prestigious IABAC Certification, globally recognised as evidence of competence in data science concepts and practical applications.
To succeed in data science training, individuals should establish a solid foundation in mathematics, statistics, and programming. Develop strong analytical skills, proficiency in languages like Python or R, and hands-on experience with tools like Hadoop or SQL databases.
Enrolling in online data science training in Ireland from DataMites provides flexibility, accessibility, a comprehensive curriculum, industry-relevant content, experienced instructors, and interactive learning, fostering a collaborative online learning environment.
The cost of data science training in Ireland with DataMites ranges from EUR 490 to EUR 1,226.
DataMites' Data Scientist Course in Ireland incorporates hands-on learning with over 10 capstone projects and a dedicated client/live project, providing practical experience with real-world applications.
Trainers at DataMites are chosen based on certifications, decades of extensive industry experience, and a demonstrated mastery of the subject matter.
DataMites offers flexible learning options, including Live Online sessions and self-study, designed to cater to individual preferences.
The Flexi-Pass option in DataMites' Certified Data Scientist Course allows participants to join multiple batches, providing flexibility to revisit topics, clarify doubts, and enhance their understanding across various sessions for a comprehensive learning experience.
Yes, DataMites issues a Certificate of Completion for the Data Science Course, validating participants' expertise in data science and contributing to enhanced credibility in the job market.
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 a participant misses a session in the Certified Data Scientist Course, they typically have the option to access recorded sessions or participate in support sessions to catch up on missed content and address any doubts.
Certainly, prospective participants at DataMites can attend a demo class before paying for the Certified Data Scientist Course in Ireland to evaluate the teaching style, course content, and overall structure.
DataMites integrates internships into its certified data scientist course in Ireland, providing a unique learning experience that combines theoretical knowledge with practical industry exposure. This approach enhances skills and increases job opportunities in the evolving field of data science.
Yes, upon completing the Data Science training, participants receive an internationally recognized IABAC® certification, affirming their proficiency in the field and enhancing their employability globally.
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.