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
The Data Science Project lifecycle involves defining objectives, collecting and preprocessing data, conducting exploratory data analysis, developing models, validating results, deploying solutions, and continually monitoring performance. Each phase is crucial for aligning the project with business goals and delivering meaningful insights.
Data Science entails deriving insights and knowledge from data through statistical analysis, machine learning, and data visualization, covering the entire data lifecycle.
Aspiring Data Scientists should possess proficiency in programming, data manipulation, statistical analysis, and machine learning. Effective communication, problem-solving, and critical thinking are also crucial.
The operational process of Data Science involves defining problems, collecting and preprocessing data, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Collaboration and communication play pivotal roles throughout the process.
The leading choice in Stockholm is the Certified Data Scientist Course. Covering essential areas like programming and machine learning, this certification equips participants with practical expertise crucial for a successful data science career.
Certification programs in Data Science are open to individuals with backgrounds in mathematics, statistics, computer science, or related fields. Professionals aiming to boost analytical skills or transition into the field also find these programs advantageous.
Statistics is foundational in data science, facilitating data analysis, hypothesis testing, and model validation. It establishes a robust framework for making informed decisions and drawing meaningful conclusions from data.
In Stockholm, a Data Scientist usually starts as an analyst, progressing to senior roles or specialized positions like a machine learning engineer. Continuous learning, networking, and gaining hands-on experience contribute to career advancement within the field.
Initiate the journey by establishing a strong foundation in mathematics and programming. Engage in practical projects, enroll in online courses, and build a portfolio showcasing your skills. Networking in the data science community and seeking mentorship are valuable for a successful initiation.
While a bachelor's degree in a related field is common, advanced degrees like a master's or Ph.D. provide an advantage. Essential requirements include relevant skills, experience, and a strong foundation in mathematics and programming.
In finance, Data Science is applied for tasks such as risk management, fraud detection, customer segmentation, and algorithmic trading. It empowers data-driven decision-making, enhances customer experiences, and contributes to the sector's efficiency and innovation.
Glassdoor reports an impressive monthly average salary of SEK 87,267 for Data Scientists in Stockholm. This robust compensation figure reflects the competitive and rewarding nature of Data Science Roles in the vibrant professional landscape of the Swedish capital.
Common challenges encompass data quality issues, model interpretability, and scalability. Mitigating solutions involve robust data preprocessing, utilizing explainable AI techniques, and optimizing algorithms for efficiency and scalability.
Data Scientists are tasked with collecting, processing, and analyzing data to extract valuable insights. They develop predictive models, craft data visualizations, and communicate findings to inform business strategies. Collaborating with cross-functional teams is vital for achieving organizational objectives.
Enrolling in Data Science Bootcamps proves valuable for swift skill acquisition, offering hands-on experience, mentorship, and networking opportunities. Successful outcomes, however, hinge on personal commitment and the overall quality of the chosen bootcamp.
Engaging in Data Science Internships provides hands-on experience with real projects, enhancing practical skills, offering exposure to industry practices, and often leading to job opportunities. Internships effectively bridge the gap between academic learning and the requirements of professional roles in data science.
Data Science analyzes customer behavior and transaction data in e-commerce to offer personalized recommendations. Powered by machine learning algorithms, recommendation systems enhance user experiences, drive engagement, and contribute to increased sales and customer satisfaction.
In finance, Data Science is crucial for risk management, fraud detection, customer segmentation, and algorithmic trading. Predictive modeling and analytics enable data-driven decision-making, ultimately enhancing efficiency and fostering innovation in the sector.
Data Science methodologies find extensive application across various industries, including finance, healthcare, e-commerce, manufacturing, telecommunications, and energy. The adaptability of data science tools and techniques contributes to improved decision-making, innovation, and operational efficiency in diverse sectors.
Data Science enhances manufacturing by predicting equipment failures and streamlines supply chain operations through improved demand forecasting and inventory management. The result is increased operational efficiency, cost reduction, and overall improved performance.
Trainers at DataMites are meticulously selected based on their elite status, with faculty members possessing real-time experience from renowned companies and prestigious institutes such as IIMs conducting the data science training sessions.
DataMites is a prominent provider of data science certifications in Stockholm, offering a diverse range to cater to various learning needs. The flagship Certified Data Scientist course forms the core of their offerings, providing a comprehensive skill set. Specialized certifications like Data Science for Managers and Data Science Associate accommodate different expertise levels.
For a well-rounded education, the Diploma in Data Science is available. DataMites extends its reach with focused courses in Statistics, Python, and domain-specific applications in Marketing, Operations, Finance, HR, fostering a dynamic and inclusive learning environment for aspiring data scientists.
Newcomers to data science in Stockholm can explore beginner-level training options. The Certified Data Scientist Course imparts foundational skills, while Data Science in Foundation introduces essential concepts. The Diploma in Data Science offers a comprehensive curriculum for beginners, ensuring a solid understanding. These courses from DataMites are tailored for beginners, providing the necessary knowledge to kickstart a successful journey in the evolving field of data science.
Absolutely, DataMites recognizes the needs of working professionals in Stockholm, offering specialized data science courses such as Statistics, Python, and Certified Data Scientist Operations. Tailored options like Data Science with R Programming and Certified Data Scientist courses for Marketing, HR, and Finance address specific professional needs, ensuring professionals acquire targeted expertise.
At the forefront of data science education, the DataMites Certified Data Scientist Course in Stockholm is globally recognized as the premier, job-oriented program in Data Science and Machine Learning. Updated consistently to meet industry standards, it ensures a structured learning process facilitating efficient skill acquisition.
The duration of DataMites' data scientist courses in Stockholm varies from 1 to 8 months, dependent on the specific program and course level.
No prerequisites are required for enrolling in the Certified Data Scientist Training in Stockholm, making it accessible to beginners and intermediate learners.
Certainly, DataMites ensures live projects as part of their Data Scientist Course in Stockholm, involving over 10 capstone projects and a substantial client/live project.
DataMites' data science training in Sweden comes with a flexible fee structure, spanning from SEK 5449 to SEK 13624. This ensures that aspiring data scientists can choose a plan that aligns with their budget while still accessing comprehensive and high-quality training.
In cases of missed data science training courses in Stockholm, recorded sessions are accessible for review. Additionally, participants have the option of scheduling one-on-one sessions with trainers to address queries and clarify concepts covered during the missed sessions, ensuring a comprehensive learning experience.
Certainly, DataMites in Stockholm provides a demo class option, allowing participants to attend a sample session and assess the training before making a commitment.
Opting for DataMites' online data science training in Stockholm provides the advantage of flexibility, enabling participants to learn from any location without geographical constraints. The interactive online platform encourages engagement through discussions, forums, and collaborative activities, enhancing the overall data science training experience.
Indeed, DataMites provides Data Science Courses with Internships in Stockholm, allowing participants to gain practical experience with AI companies.
Managers and leaders aiming to integrate data science into decision-making processes can benefit from the "Data Science for Managers" course at DataMites.
Upon completing Data Science Training in Stockholm at DataMites, participants receive IABAC Certification, affirming their proficiency in data science.
In Stockholm, DataMites' Flexi-Pass introduces flexibility to the data science training schedule, allowing participants to customize their learning journey based on their availability and preferences.
Career mentoring sessions at DataMites in Stockholm follow a comprehensive format, covering resume crafting, interview techniques, and industry trends to empower participants for a successful entry into the data science field.
DataMites in Stockholm offers data science courses through online data science training in Stockholm and self-paced options, providing flexibility and personalized learning for participants.
Certainly, participants in Stockholm have the option of attending help sessions with DataMites, providing targeted assistance for a better understanding of specific data science topics.
Certainly, participants attending data science training sessions in Stockholm must bring a valid photo identification proof, such as a national ID card or driver's license, for the issuance of participation certificates and to facilitate any certification exams.
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.