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 practice of extracting insights and knowledge from data using methods like statistical analysis, machine learning, and data visualization. It encompasses the entire data lifecycle, from collection to interpretation.
The preferred choice in Sweden is the Certified Data Scientist Course. Covering essential areas like programming and machine learning, this certification ensures participants gain practical expertise for a successful career in data science.
Essential skills for aspiring Data Scientists include proficiency in programming, data manipulation, statistical analysis, and machine learning. Effective communication, problem-solving, and critical thinking are also key for success in the field.
While a bachelor's degree in a related field is common, advanced degrees like a master's or Ph.D. are advantageous. Essential prerequisites include relevant skills, practical experience, and a strong foundation in mathematics and programming.
The operational process includes defining the problem, collecting and preprocessing data, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Collaboration and communication play integral roles throughout this process.
In Sweden, a Data Scientist typically starts as an analyst, advancing to senior roles or specialized positions like a machine learning engineer. Career progression involves continuous learning, networking, and gaining practical experience within the field.
Certification programs in Data Science are accessible to those with backgrounds in mathematics, statistics, computer science, or related fields. Professionals aiming to enhance their analytical skills or transition into the field also find these programs valuable.
Statistics is foundational in data science, assisting in data analysis, hypothesis testing, and model validation. It establishes a robust framework for informed decision-making and drawing meaningful conclusions from data.
Initiate the journey by building a strong foundation in mathematics and programming. Engage in hands-on projects, participate in online courses, and create a portfolio showcasing your skills. Networking within the data science community and seeking mentorship contribute to a successful start.
Common challenges include data quality, model interpretability, and scalability. Solutions involve robust data preprocessing, the application of explainable AI techniques, and optimizing algorithms for efficiency and scalability.
In finance, Data Science is utilized for risk management, fraud detection, customer segmentation, and algorithmic trading. It facilitates data-driven decision-making, improves customer experiences, and enhances efficiency and innovation within the sector.
Engaging in Data Science Internships provides practical exposure to real-world projects, enhancing hands-on skills and often leading to job opportunities. Internships bridge the gap between academic learning and the demands of professional data science roles.
Data Scientists are accountable for collecting, processing, and analyzing data to derive valuable insights. They develop predictive models, create data visualizations, and communicate findings to shape business strategies. Collaborating with cross-functional teams is crucial for achieving organizational objectives.
In finance, Data Science is instrumental for risk management, fraud detection, customer segmentation, and algorithmic trading. Predictive modeling and analytics facilitate data-driven decision-making, ultimately enhancing operational efficiency and fostering innovation in the sector.
The Data Science project lifecycle encompasses defining objectives, collecting and preprocessing data, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Each phase is vital for ensuring alignment with business goals and delivering meaningful insights.
Engaging in Data Science Bootcamps proves valuable for swift skill acquisition, offering hands-on experience, mentorship, and networking for accelerated entry into the field. However, success depends on personal commitment and the overall quality of the chosen bootcamp.
Data Science enhances manufacturing by predicting equipment failures and streamlines supply chain operations through improved demand forecasting and inventory management. It leads to heightened efficiency, cost reduction, and overall operational improvements.
In e-commerce, Data Science analyzes customer behavior and transaction data to deliver personalized recommendations. Powered by machine learning algorithms, recommendation systems elevate user experiences, boost customer engagement, and increase sales and satisfaction.
Data Science methodologies find widespread application in diverse industries, including finance, healthcare, e-commerce, manufacturing, telecommunications, and energy. The adaptability of data science tools contributes to enhanced decision-making, innovation, and operational efficiency across various sectors.
Levels.fyi reports an enticing average salary of SEK 488,821 for Data Scientists in Sweden. This noteworthy compensation range reflects the lucrative nature of Data Science roles in the Swedish job market, indicating competitive remuneration for professionals in the field.
Trainers at DataMites are meticulously chosen for their elite status, comprising faculty members with real-time experience from renowned companies and prestigious institutions like IIMs who lead the data science training sessions.
For newcomers, DataMites offers accessible beginner-level training options. The Certified Data Scientist Course in Sweden provides foundational skills, while Data Science in Foundation introduces essential concepts. The Diploma in Data Science offers a comprehensive curriculum, ensuring a solid understanding. These courses cater to beginners, providing the necessary knowledge to embark on a successful journey in the evolving field of data science.
Indeed, DataMites recognizes the needs of working professionals in Sweden, 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 targeted expertise for professionals.
The DataMites Certified Data Scientist Course in Sweden stands at the forefront of data science education, acknowledged as the world's premier, job-oriented program in Data Science and Machine Learning. This course is regularly updated to align with industry standards, ensuring a structured learning process that facilitates efficient skill acquisition.
The duration of DataMites' data scientist courses in Sweden varies from 1 to 8 months, dependent on the course level and specific program.
Enrolling in the Certified Data Scientist Training in Sweden requires no prerequisites, making it accessible for beginners and intermediate learners in data science.
Certainly, DataMites ensures live projects as part of their Data Scientist Course in Sweden, featuring over 10 capstone projects and a hands-on client/live project.
The fee structure for DataMites' data science training in Sweden ranges from SEK 5449 to SEK 13624. This diverse range ensures accessibility for participants with varying budget constraints, offering affordable options for quality data science education.
Certainly, participants attending data science training sessions in Sweden should bring a valid photo identification proof, like a national ID card or driver's license. This facilitates the issuance of participation certificates and scheduling certification exams if applicable.
Certainly, in Sweden, DataMites provides a trial class option, allowing participants to experience a sample session and assess the training before making a commitment.
DataMites' online data science training in Sweden provides the advantage of flexibility, allowing participants to learn from any location without geographical constraints. The interactive online platform encourages engagement through discussions, forums, and collaborative activities, enriching the overall data science training experience.
Certainly, DataMites offers Data Science Courses with Internships in Sweden, providing participants with hands-on experience with AI companies.
For managers and leaders looking to integrate data science into decision-making processes, "Data Science for Managers" at DataMites is the ideal choice.
Upon completion of Data Science Training in Sweden at DataMites, participants are awarded the IABAC Certification, validating their proficiency in data science.
DataMites acknowledges that participants may miss a training session in Sweden and provides recorded sessions for review. Additionally, one-on-one sessions with trainers are available to address queries and clarify concepts covered during the missed session, ensuring a comprehensive learning experience.
In Sweden, DataMites' Flexi-Pass introduces flexibility to the data science training schedule, allowing participants to customize their learning journey based on their availability and preferences.
DataMites in Sweden offers various training methods for data science courses, including online data science training in Sweden and self-paced options, providing flexibility and personalized learning opportunities.
Certainly, in Sweden, DataMites provides help sessions for participants, offering targeted support and clarification on specific data science topics.
Career mentoring sessions at DataMites in Sweden follow a comprehensive format, covering resume building, data science interview techniques, and industry trends to prepare participants for a successful entry into the data science field.
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.