DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN LISBON, PORTUGAL

Live Virtual

Instructor Led Live Online

PTE 1,860
PTE 1,055

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

PTE 930
PTE 604

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA ANALYST ONLINE CLASSES IN LISBON

BEST DATA ANALYTICS CERTIFICATIONS

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.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN LISBON

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain

MODULE 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

MODULE 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
Modeling, Evaluation, Deploying,Monitoring

MODULE 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

MODULE 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

  • Introduction to Statistics
  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's Minimum Sample Size
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of Hypothesis testing

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis

MODULE 3: RANKING ANALYSIS

• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis

MODULE 4: BREAK EVEN ANALYSIS

• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis

MODULE 6: Time Series and Trend Analysis

• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

MODULE 1: MACHINE LEARNING INTRODUCTION

• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION

• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool

MODULE 3: ML ALGO: LOGISTIC REGRESSION

• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool

MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

MODULE 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)

MODULE 2: SQL BASICS

• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS

• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL)

• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table

MODULE 5: SQL JOINS

• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank

MODULE 6: SQL COMMANDS AND CLAUSES

• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries

MODULE 7: DOCUMENT DB/NO-SQL DB

• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS

• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies

MODULE 2: POWER-BI BASICS

• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION

MODULE 3: DATA TRANSFORMATION TECHNIQUES

• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES

• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model

OFFERED DATA ANALYST COURSES IN LISBON

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN LISBON

Lisbon, the vibrant capital of Portugal, mirrors the global momentum in Data Analytics. Marked by dynamic growth, the industry stands as a pivotal force in Lisbon's tech landscape. In sync with the global market, which reached USD 254.6 billion in 2022 and is projected to hit USD 808.5 billion by 2031, Lisbon's Data Analytics sector is flourishing. The city stands at the forefront of technological evolution, providing an ideal environment for professionals to engage in the transformative and dynamic world of data-driven insights.

In Lisbon, Portugal's bustling capital, DataMites emerges as a leading global institute for Data Analytics training. Our Certified Data Analyst Course in Lisbon, tailored for beginners and intermediate learners, is a career-centric program designed to establish a strong foundation in Data Analysis, Data Science, Statistics, Visual Analytics, Data Modeling, and Predictive Modeling. Elevate your expertise with a curriculum curated for success, culminating in IABAC Certification. DataMites in Lisbon is your pathway to a thriving career, offering a holistic learning experience in the dynamic realm of Data Analytics.

In Lisbon, DataMites introduces a meticulously designed three-phase Certified Data Analyst Training in Lisbon;

Phase 1: Pre Course Self-Study

Embark on your educational journey with high-quality videos employing an easy-to-understand learning approach.

Phase 2: 3-Month Duration

Immerse yourself in live training sessions, committing 20 hours per week to a comprehensive syllabus. Participate in hands-on projects guided by seasoned trainers and mentors.

Phase 3: 3-Month Duration

Elevate your skills through project mentoring, completing 5+ capstone projects, engaging in real-time internships, and contributing to a live client project. Attain IABAC and data analytics internship certifications, solidifying your expertise in the dynamic realm of Data Analytics in Lisbon.

Certified Data Analyst Courses in Lisbon - Features

where excellence meets expertise in the realm of Data Analytics and AI education, led by the distinguished Ashok Veda. With a remarkable 19 years of seasoned experience in the field, Ashok Veda, also the Founder & CEO at Rubixe™, spearheads our commitment to providing unparalleled education in Data Analytics.

  1. Course Highlights: Embark on a transformative learning journey with our NO-CODE PROGRAM (OPTIONAL PYTHON), a comprehensive 6-month program designed for your success.
  2. Time Commitment: Dedicate 20 hours a week to enrich your knowledge, accumulating a total of 200+ learning hours.
  3. Global Recognition: Attain the prestigious IABAC® Certification, propelling your career to new heights.
  4. Flexibility: Experience the convenience of online data analytics courses in Lisbon and self-study, tailored to accommodate your schedule.
  5. Real-world Application: Immerse yourself in practical learning with our hands-on approach:
  6. Projects and Internship Opportunity: Engage in 5+ CAPSTONE PROJECTS, allowing you to apply your skills in real-world scenarios.Work on a CLIENT/LIVE PROJECT, gaining invaluable industry exposure.
  7. Career Advancement: We go beyond education to empower your career. Benefit from End-to-End job support, personalized resume building, and data analytics interview preparation. Stay informed with job updates and connections facilitated by our dedicated support team.
  8. Exclusive Learning Community: Join the vibrant DataMites community, fostering collaborative learning and professional growth.
  9. Affordability: Avail our courses at affordable rates, with Data Analytics course fees in Portugal ranging from PTE 78351 to PTE 240926.

Lisbon's Data Analytics sector is experiencing a dynamic surge, making it a thriving hub for professionals seeking growth. The city's tech landscape, coupled with a burgeoning startup culture, presents abundant opportunities for Data Analytics enthusiasts.

In this landscape, Data Analysts in Lisbon command lucrative salaries, with an average monthly income of $1380 according to Glassdoor. This highly competitive remuneration reflects the industry's recognition of the pivotal role Data Analysts play in shaping business strategies and fueling innovation. Such substantial compensation underlines the industry's acknowledgment of the vital contributions made by skilled professionals in this data-driven era.

Navigate Lisbon's dynamic tech landscape with DataMites, a cornerstone in data education. Go beyond Data Analytics Training in Lisbon into courses like Python, Tableau, Data Science, Machine Learning, Data Engineering, Artificial Intelligence, and more. Our programs are designed to match Lisbon's industry needs, empowering you for the competitive market. Experience affordability and excellence, positioning yourself for success in Lisbon's burgeoning tech sector. 

ABOUT DATAMITES DATA ANALYST COURSE IN LISBON

Data analytics involves the exploration, interpretation, and visualization of datasets to extract insights and inform decision-making. It encompasses various techniques such as statistical analysis, data mining, and machine learning to derive meaningful information from structured and unstructured data sources.

A data analyst typically undertakes tasks like collecting and cleaning data, performing statistical analysis, creating data visualizations, and generating reports. They interpret findings, identify trends, and communicate insights to stakeholders, contributing to data-driven decision-making in organizations.

Success in data analytics requires proficiency in programming and statistical analysis, critical thinking, problem-solving, and effective communication. Additionally, adaptability to new technologies and methodologies, attention to detail, and domain knowledge are essential for navigating the dynamic field of data analytics.

Data analytics enhances marketing strategies by analyzing customer behavior, preferences, and trends. It enables targeted advertising, personalized messaging, and segmentation strategies based on demographic, psychographic, and behavioral data. By understanding consumer insights, marketers can optimize marketing campaigns, improve customer engagement, and enhance return on investment.

Key roles in data analytics include data analyst, data scientist, business analyst, data engineer, and machine learning engineer. Each role specializes in different aspects of data collection, analysis, interpretation, and application, contributing to organizational decision-making and strategy formulation.

Key tools for data analytics include programming languages like Python or R, data visualization libraries such as Matplotlib or Seaborn, statistical packages like Pandas or NumPy, and database querying languages such as SQL. Hands-on experience with these tools is crucial for practical application and skill development in data analytics.

Examples include predicting customer churn for telecom companies, optimizing inventory management for retail businesses, detecting fraudulent transactions in financial services, healthcare analytics for patient diagnosis, and trend forecasting in financial markets. These applications demonstrate the diverse and impactful uses of data analytics across industries.

Data analytics improves healthcare operations by enabling predictive analytics for disease prevention, personalized treatment plans, and population health management. It optimizes resource allocation, patient flow, and quality assessment, ultimately leading to improved patient outcomes and cost-effective healthcare delivery.

Data analytics coursework can be challenging due to its interdisciplinary nature, requiring proficiency in statistics, programming, and data manipulation. Students often face complex datasets and analytical techniques, necessitating critical thinking and problem-solving skills to derive meaningful insights.

While significant progress can be made in six months with dedicated study and practice, mastery in data analytics typically requires continuous learning and practical experience. With structured learning resources, hands-on projects, and focused effort, individuals can develop foundational skills within this timeframe.

In Lisbon, Data Analysts earn lucrative salaries, with an average monthly income of $1380, as reported by Glassdoor.

Internships provide hands-on experience with real-world data sets and tools, crucial for acquiring practical data analytics skills. They offer exposure to industry practices, mentorship, and networking opportunities, accelerating skill development and enhancing employability.

Big data analytics differs from other forms of data analysis in its focus on processing and analyzing large and complex datasets. It involves techniques and technologies for handling massive volumes of data characterized by the three Vs: volume, velocity, and variety, to derive meaningful insights for decision-making.

While coding is integral to data analytics, the extent varies. Basic proficiency in languages like Python or R is necessary for data manipulation and analysis. Extensive coding may be required for algorithm development and advanced analytics tasks, depending on the complexity of projects.

DataMites provides prestigious data analytics courses, such as Certified Data Analyst Training - No coding. With a focus on practical learning and industry relevance, students develop crucial skills for a successful data analytics career.

Advancements like artificial intelligence, big data processing, and cloud computing revolutionize data analytics. They enable faster processing, deeper insights, and automation, leading to greater efficiency and innovation in decision-making.

AI enhances data analytics by automating processes, detecting patterns, and making predictions. Machine learning algorithms enable predictive modeling, anomaly detection, and natural language processing, augmenting the capabilities of data analytics.

Data analytics optimizes supply chains by improving demand forecasting, inventory management, and logistics. Real-time insights enhance efficiency and responsiveness to market demands.

Steps include handling missing values, removing duplicates, standardizing formats, and transforming variables. Outlier detection and normalization ensure data quality for analysis.

Typically, a background in mathematics, statistics, or computer science is preferred. Proficiency in programming languages like Python or R and familiarity with data analysis tools may also be required.

View more

FAQ’S OF DATA ANALYST TRAINING IN LISBON

DataMites is your ideal choice for the Certified Data Analyst Course in Lisbon, offering flexible learning, industry-aligned curriculum, expert mentors, exclusive practice lab facilities, collaborative learning environment, and lifelong access to resources. With hands-on projects and career placement aid, DataMites empowers you for a successful data analytics career.

Absolutely, upon fulfilling the requirements of the Certified Data Analyst Course in Lisbon at DataMites, participants will receive the esteemed IABAC Certification. This globally recognized accreditation affirms their competence in data analytics, amplifying their career opportunities and distinguishing them as proficient data analysts in the field.

Individuals at the beginner or intermediate level in data analytics are eligible for DataMites' Certified Data Analyst Training in Lisbon. The program focuses on essential aspects like data analysis, statistics, visual analytics, and predictive modeling, empowering participants for successful careers in the field.

DataMites' Data Analyst Course in Lisbon is designed as a 6-month program, with participants devoting 20 hours per week to learning. Featuring over 200 learning hours, the course provides in-depth training in data analytics for career growth.

DataMites' certified data analyst training in Lisbon provides instruction on Google Collab, Numpy, and Tableau for advanced data analysis and visualization techniques.

DataMites' Certified Data Analyst Course in Lisbon is structured for advanced analytics and business insights, offering a NO-CODE program that enables participants, including data analytics professionals and managers, to excel without prior programming expertise.

The fee structure for DataMites' Data Analytics Course in Lisbon ranges from PTE 78,351 to PTE 240,926. This course provides participants with comprehensive training in data analytics, empowering them with essential skills to thrive in the field and meet the demands of the industry effectively.

Absolutely, DataMites is dedicated to providing support to help participants understand data analytics course topics in Lisbon. With experienced instructors, engaging learning resources, personalized mentorship sessions, and a collaborative learning atmosphere, participants receive tailored assistance to enhance their understanding and excel in the program.

Participants in the Certified Data Analyst Training in Lisbon will delve into critical topics such as Data Analysis Foundation, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, Database Management through SQL and MongoDB, Version Control with Git, Big Data Foundation, Python Foundation, and Certified Business Intelligence (BI) Analyst.

Accepted payment methods for the Certified Data Analytics Course at DataMites in Lisbon comprise cash, debit card, check, credit card, EMI, PayPal, Visa, Mastercard, American Express, and net banking.

The Certified Data Analyst Course in Lisbon at DataMites is conducted by Ashok Veda and elite mentors with expertise in Data Science and AI. Trainers bring invaluable insights and guidance to participants, leveraging their real-world experience from leading companies and prestigious institutes such as IIMs.

DataMites' Flexi Pass for the Certified Data Analyst Course in Lisbon offers participants the flexibility to design their learning experience. This option enables learners to access course content and attend sessions according to their availability, empowering them to balance their studies with their other obligations effectively.

At DataMites, the Certified Data Analyst Course in Lisbon is delivered through a case study-oriented approach. Participants delve into real-world data scenarios, applying data analysis methodologies to extract meaningful insights. This hands-on learning methodology fosters critical thinking and prepares learners to address data-related challenges in their careers.

Should you be unable to attend a data analytics session in Lisbon, DataMites provides session recordings for flexible playback. Additionally, comprehensive study materials and resources are available to help you grasp any missed concepts. This ensures you remain on track with the course curriculum and learning outcomes.

For attending the training session, participants must present a valid photo identification proof, such as a national ID card or driver's license. This documentation is essential for receiving the participation certificate and arranging any certification exams. Ensuring compliance with this requirement facilitates a smooth and organized training experience.

DataMites in Lisbon conducts structured data analytics career mentoring sessions to offer personalized guidance and support to participants. Through one-on-one meetings with seasoned mentors, individuals receive tailored career advice, insights, and strategies to help them progress in their careers in the data analytics field.

Indeed, DataMites' Certified Data Analyst Course holds significant value in Lisbon. It's the most comprehensive non-coding course, allowing individuals from non-technical backgrounds to pursue data analytics careers. With a three-month internship at an AI company, experience certificate, and prestigious IABAC Certification, participants secure industry recognition and career advancement.

Yes, DataMites offers internships alongside the Certified Data Analyst Programme in Lisbon. Learners have the chance to gain practical experience through collaborations with top Data Science firms. This internship program enables them to apply their knowledge in real-world projects, supported by DataMites experts, fostering professional growth and industry competency.

Absolutely, DataMites ensures live projects are part of the data analyst course in Lisbon. Participants undertake 5+ capstone projects and contribute to 1 client/live project. These practical engagements provide learners with valuable exposure to real-world scenarios, allowing them to develop and refine their data analytics skills effectively.

DataMites provides a range of learning methods for its data analytics courses in Lisbon, including online data analytics training in Lisbon and self-paced learning. Participants can choose to attend interactive online sessions or progress through course materials independently, offering flexibility and convenience to accommodate diverse learning preferences and schedules.

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: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

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.

View more

Global DATA ANALYTICS COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog