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 landscape is a vast terrain, incorporating machine learning, statistics, and data analysis, converging to extract insights crucial for informed decision-making.
The convergence of Big Data and Data Science occurs in the management and analysis of extensive datasets, with Big Data emphasizing specialized tools designed for handling large volumes of data.
While coding is advantageous, individuals without coding experience can enter the Data Science field through platforms that require little to no coding.
Educational qualifications typically include a bachelor's or master's degree in fields such as computer science, statistics, or mathematics.
Aspiring Data Scientists should possess programming skills (e.g., Python), statistical knowledge, machine learning expertise, data visualization skills, and strong problem-solving abilities.
Building a compelling portfolio involves showcasing real-world projects, emphasizing problem-solving skills, and demonstrating proficiency in relevant tools and techniques.
Proficiency in Python is often deemed essential for Data Science roles due to its prevalence in data analysis, machine learning, and the development of data pipelines.
The typical career path in Brussels may involve roles such as Data Analyst, Junior Data Scientist, Senior Data Scientist, with potential advancement into managerial positions.
Enrollment is generally open to individuals with a background in mathematics, statistics, computer science, or related fields.
Initial steps include gaining foundational knowledge, acquiring relevant technical skills, and establishing connections with local professionals and organizations.
Compensation for Data Scientists in Brussels varies based on factors like experience, skills, and industry. On average, the annual salary falls within the range of EUR 6,000.
Constructing a compelling portfolio for a Data Science role involves showcasing a variety of projects, highlighting technical skills, and providing clear explanations of methodologies and outcomes.
The demand for Data Scientists in Brussels is particularly high in tech hubs like Silicon Valley, financial centers, and the healthcare sector on a global scale.
Current trends in Data Science include the rise of explainable AI, automated machine learning, and a growing emphasis on ethical considerations in AI applications.
In Brussels, a postgraduate degree is not always a requirement for data science training programs. Many programs accept candidates based on relevant experience and skills.
The Data Science workflow comprises stages such as data collection, cleaning, exploration, modeling, validation, and deployment, with iterative steps for continuous improvement.
In Brussels, Data Science contributes to business growth by improving decision-making, providing customer insights, and optimizing operations, ultimately enhancing competitiveness.
For data science training in Brussels, the Certified Data Scientist Course stands out, covering essential topics such as machine learning and data analysis.
Data Science finds applications in various industries in Brussels, including finance, healthcare, e-commerce, and telecommunications. It contributes to predictive analytics, fraud detection, and personalized marketing.
Data Science involves extracting insights from data, while Machine Learning, as a subset, focuses on training models to make predictions or decisions based on data.
The DataMites Certified Data Scientist Course in Brussels is a globally recognized program that delves into Data Science and Machine Learning. It undergoes regular updates to stay aligned with industry requirements, ensuring a structured and targeted learning experience.
DataMites in Brussels extends a variety of certifications, including the 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.
For beginners in Brussels, entry-level training options encompass courses such as Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science.
Certainly, DataMites in Brussels offers specialized courses like 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 duration of DataMites' data scientist course in Brussels varies, ranging from 1 month to 8 months, contingent on the specific level of the course.
Enrollment in the Certified Data Scientist Training in Brussels is open to beginners and intermediate learners in the field of data science, with no specific prerequisites.
Choosing online data science training in Brussels from DataMites brings benefits such as flexibility, accessibility, a comprehensive curriculum, industry-relevant content, expert instructors, and interactive learning experiences.
The DataMites' data science training fee in Brussels ranges from EUR 488 to EUR 1220, offering affordable options for quality education in the field.
Instructors at DataMites are chosen based on certifications, extensive industry experience, and expertise in the subject to ensure high-quality training sessions.
Yes, participants are required to 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.
Participants in the DataMites course have the flexibility to access recorded sessions or attend support sessions if they miss a class. This ensures that they can review missed content, clarify doubts, and stay on track with the course.
Prospective participants in the Certified Data Scientist Course in Brussels can attend a demo class before making any payment. This allows them to evaluate the teaching style, course content, and overall structure.
Yes, DataMites integrates internships into its Certified Data Scientist Course in Brussels, providing a comprehensive learning experience that combines theoretical knowledge with practical industry exposure.
Tailored for managers and leaders, the "Data Science for Managers" course at DataMites equips them with skills to seamlessly integrate data science into decision-making processes, fostering informed and strategic choices.
Certainly, participants in Brussels can opt to attend help sessions, offering a valuable opportunity for a deeper understanding of specific data science topics, ensuring a comprehensive learning experience.
Indeed, DataMites' Data Scientist Course in Brussels includes hands-on learning with over 10 capstone projects and a dedicated client/live project. This provides practical experience and industry-relevant exposure.
Yes, DataMites provides a Data Science Course Completion Certificate. Upon successful completion, participants can request the certificate through the online portal, validating their proficiency in data science.
The Flexi-Pass feature in DataMites' Certified Data Scientist Course allows participants to enroll in multiple batches, providing flexibility to revisit topics, address uncertainties, and deepen comprehension through various sessions.
DataMites' career mentoring sessions follow an interactive format, offering personalized guidance on resume building, interview preparation, and career strategies. These sessions provide valuable insights to enhance participants' professional journey in data science.
DataMites in Brussels provides live online training, enabling real-time interaction with instructors for an engaging learning environment. Participants can also access recorded sessions at their convenience, allowing for a personalized learning pace to optimize outcomes.
Upon successful completion of the Data Science training, you will receive an internationally recognized IABAC® certification, validating your 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.