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 spans machine learning, statistics, and data analysis, converging to derive insights crucial for well-informed decision-making.
The intersection of Big Data and Data Science lies in managing and analyzing extensive datasets, with Big Data emphasizing tools tailored for handling voluminous data.
While coding is beneficial, those without coding experience can enter Data Science through no-code/low-code platforms.
Educational qualifications often include a bachelor's or master's degree in fields like 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 an impactful portfolio involves showcasing real-world projects, emphasizing problem-solving skills, and demonstrating proficiency in relevant tools and techniques.
Proficiency in Python is often considered vital for Data Science roles due to its prevalence in data analysis, machine learning, and building data pipelines.
The standard career path in Belgium may include roles such as Data Analyst, Junior Data Scientist, Senior Data Scientist, with potential progression to 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 networking with local professionals and organizations.
Belgium Compensation for Data Scientists in Belgium varies based on experience, skills, and industry, with an average annual salary range of EUR 45,140.
Belgium Crafting an impactful portfolio involves showcasing diverse projects, emphasizing technical skills, and providing clear explanations of methodologies and outcomes.
Belgium's Demand for Data Scientists is notably high in tech hubs like Silicon Valley, financial centers, and the healthcare sector on a global scale.
Belgium Current trends include explainable AI, automated machine learning, and an increased emphasis on ethical considerations within AI applications.
Belgium A postgraduate degree is not always a requirement; many programs in Belgium accept candidates based on relevant experience and skills.
Belgium The Data Science workflow encompasses data collection, cleaning, exploration, modeling, validation, and deployment, with iterative steps for continuous improvement.
Belgium Data Science in Belgium enhances business growth through improved decision-making, customer insights, and optimized operations, thereby increasing competitiveness.
Belgium The Certified Data Scientist Course is a top-tier option for data science training in Belgium, covering crucial topics like machine learning and data analysis.
Belgium Data Science finds applications in industries such as finance, healthcare, e-commerce, and telecommunications, contributing to predictive analytics, fraud detection, and personalized marketing.
Belgium Data Science focuses on extracting insights from data, while Machine Learning, as a subset, involves training models to make predictions or decisions based on data.
The DataMites Certified Data Scientist Course in Belgium is a globally recognized program covering Data Science and Machine Learning, regularly updated to align with industry needs, ensuring a systematic and focused learning experience.
DataMites in Belgium offers certifications like 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.
Entry-level training options for beginners in Belgium include courses like Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science.
Yes, DataMites in Belgium 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 Belgium varies from 1 month to 8 months, depending on the specific level of the course.
Enrollment in the Certified Data Scientist Training in Belgium is open to beginners and intermediate learners in the field of data science, with no specific prerequisites.
Online data science training in Belgium from DataMites provides advantages like adaptability, accessibility, a comprehensive curriculum, industry-relevant content, expert instructors, and interactive learning experiences.
The DataMites' data science training fee in Belgium ranges from EUR 488 to EUR 1220 offering affordable options for quality education in the field.
Instructors at DataMites are selected based on certifications, extensive industry experience, and subject mastery 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 they can review missed content, clarify doubts, and stay on track with the course.
Certainly, prospective participants in the Certified Data Scientist Course in Belgium can attend a demo class before making any payment, allowing them to evaluate the teaching style, course content, and overall structure.
Yes, DataMites integrates internships into its Certified Data Scientist Course in Belgium, offering a comprehensive learning experience that blends theoretical knowledge with practical industry exposure.
Specifically designed 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 Belgium can choose to attend help sessions, providing a valuable opportunity for a deeper understanding of specific data science topics, ensuring a comprehensive learning experience.
Indeed, DataMites' Data Scientist Course in Belgium encompasses hands-on learning with over 10 capstone projects and a dedicated client/live project, providing 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, offering flexibility to revisit topics, address uncertainties, and deepen comprehension through various sessions.
DataMites' career mentoring sessions adopt an interactive format, providing personalized guidance on resume building, interview preparation, and career strategies. These sessions offer valuable insights to enhance participants' professional journey in data science.
DataMites in Belgium 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.