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 field focused on extracting insights and knowledge from data through methods such as statistics, machine learning, and data analysis.
Data Science operates by collecting, processing, and analyzing large datasets to unveil meaningful patterns and insights, facilitating informed decision-making across various industries.
Data Science finds applications in predictive modeling, machine learning, and data-driven decision-making across industries such as healthcare, finance, marketing, and more.
Key components of a Data Science pipeline include data collection, preprocessing, exploratory data analysis, feature engineering, model training, evaluation, and deployment.
Big Data is closely linked to Data Science, dealing with large and complex datasets that require specialized tools and techniques for analysis.
Data Science is applied across various industries, including healthcare for predictive analytics, finance for risk assessment, and e-commerce for personalized recommendations.
A career in Data Science often requires an educational background in computer science, statistics, or a related field, with expertise in programming and data manipulation.
Essential skills for a Data Scientist include programming, statistical analysis, machine learning, and effective communication.
Building a strong Data Science portfolio involves showcasing projects that demonstrate practical application of skills, problem-solving, and creativity.
Industries actively seeking Data Scientists include technology, finance, healthcare, and e-commerce.
Emerging trends in Data Science encompass explainable AI, automated machine learning, and the integration of data ethics.
The data science job market in Denmark in 2024 is shaped by industry demand and technological advancements.
Recognized as a leading choice for data science training in Denmark, the Certified Data Scientist Course covers crucial topics such as machine learning and data analysis.
Data science internships in Denmark can provide significant value by offering practical experience and opportunities for networking.
Freshers can feasibly pursue a data science course and secure employment in Denmark by building a strong skill set and incorporating relevant projects into their portfolio.
Denmark businesses harness data science for growth by utilizing analytics to gain customer insights, optimizing processes, and making strategic decisions.
In finance, data science applications encompass fraud detection, risk assessment, and algorithmic trading.
Data science contributes to e-commerce by powering recommendation systems, personalizing user experiences, and optimizing supply chain management.
In cybersecurity, data science plays a crucial role in detecting anomalies, identifying potential threats, and enhancing overall security measures.
In manufacturing and supply chain management, data science is applied for demand forecasting, inventory optimization, and improving process efficiency.
The Datamites™ Certified Data Scientist course is meticulously crafted, covering key aspects of data science, including programming, statistics, machine learning, and business knowledge. Emphasizing Python as the primary language, it also includes R for those familiar. The comprehensive curriculum ensures a strong foundation and successful completion leads to the IABAC™ certificate.
While a statistical background can be advantageous, it's not always a prerequisite for a data science career in Denmark. Proficiency in relevant tools, programming languages, and practical problem-solving skills are often prioritized.
In Denmark, DataMites offers a 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 Denmark, options include courses such as Certified Data Scientist, Data Science Foundation, and Diploma in Data Science for foundational training in data science.
Yes, DataMites in Denmark provides various courses tailored for professionals looking to enhance their expertise, including 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 Denmark 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. These sessions provide valuable insights to enrich the professional journey of participants in the field of data science.
Upon completing DataMites' Data Science Training in Denmark, participants receive the prestigious IABAC Certification. This globally recognized certification serves as evidence of their competence in both theoretical concepts and practical applications of data science, enhancing their credibility in the field.
To excel in data science, a solid foundation in mathematics, statistics, and programming is crucial. Developing strong analytical skills, proficiency in languages like Python or R, and hands-on experience with tools like Hadoop or SQL databases is recommended.
Opting for online data science training in Denmark provides flexibility, accessibility, a comprehensive curriculum aligned with industry needs, industry-relevant content, experienced instructors, interactive learning, and the ability to learn at one's own pace.
The data science training fee in Denmark varies between DKK 3,296 to DKK 9,110 depending on the specific program.
Certainly, DataMites offers a Data Scientist Course in Denmark, incorporating practical learning with over 10 capstone projects and a dedicated client/live project for hands-on experience and real-world applications.
Trainers at DataMites are selected based on certifications, extensive industry experience, and expertise in the subject matter.
DataMites offers flexible learning methods, including Live Online sessions and self-study, tailored to participants' preferences.
The FLEXI-PASS option in DataMites' Certified Data Scientist Course allows participants to join multiple batches, enabling them to review topics, address doubts, and solidify comprehension across various sessions for a comprehensive understanding of the course content.
Certainly, upon successful completion of DataMites' Data Science Course, participants can obtain a Certificate of Completion by requesting it through the online portal. This certification serves as validation of their proficiency in data science, enhancing their credibility in the job market.
Yes, 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 needed.
In case of a missed session in the DataMites Certified Data Scientist Course in Denmark, participants usually have the option to access recorded sessions or attend support sessions to make up for missed content and clarify doubts.
Yes, potential participants at DataMites can attend a demo class before making any payment for the Certified Data Scientist Course in Denmark to assess the teaching style, course content, and overall structure.
Yes, DataMites incorporates internships into its certified data scientist course in Denmark, providing a unique learning experience that combines theoretical knowledge with practical industry exposure, enhancing skills and job opportunities in the dynamic field of data science.
Upon completing the Data Science training, you will be granted an internationally recognized IABAC® certification. This certification confirms your proficiency in the field and elevates your employability on a global level.
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.