DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN FRANCE

Live Virtual

Instructor Led Live Online

FF 1,850
FF 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

FF 930
FF 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

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UPCOMING DATA ANALYST ONLINE CLASSES IN FRANCE

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.

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WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN FRANCE

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 FRANCE

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN FRANCE

Data Analytics in France, a nation witnessing the global predictive analytics market's ascent from USD 10.2 billion in 2022 to an anticipated USD 67.86 billion by 2032. This substantial growth, marked by a remarkable Compound Annual Growth Rate (CAGR) of 21.4%, positions France as a hub of technological innovation. The Data Analytics industry in France is expanding, creating a demand for skilled professionals. Now is the opportune moment to start your journey into data analytics, mastering the skills that align with the industry's upward trajectory.

In France, DataMites stands as a premier institute for Data Analytics, offering a Certified Data Analyst Course in France tailored for beginners and intermediate learners. This career-oriented data analytics program is meticulously designed to instill a robust foundation in Data Analysis, Data Science Foundation, Statistics, Visual Analytics, Data Modeling, and Predictive Modeling. Our commitment to excellence is underscored by the inclusion of IABAC Certification, validating the proficiency of participants. With a focus on providing a comprehensive learning experience, DataMites positions aspiring professionals for success in the dynamic and evolving landscape of Data Analytics in France.

DataMites: Comprehensive Data Analytics Training in France

Before delving into our offerings, it's crucial to understand the meticulous structure of our certified data analyst training in France, divided into three phases:

Phase 1: Pre-Course Self-Study

Embark on your learning journey with high-quality videos designed for an easy learning approach. This preliminary phase ensures you are well-prepared for the subsequent training.

Phase 2: 3-Month Live Training

Dive into a focused three-month live training period, committing 20 hours per week. With a comprehensive syllabus, hands-on projects, and guidance from expert trainers and mentors, this phase lays the groundwork for practical skills.

Phase 3: 3-Month Project Mentoring

Advance your skills through a three-month project mentoring phase, engaging in 5+ capstone projects, a real-time internship, and a client/live project. Successful completion leads to IABAC and data analytics internship certification, validating your expertise.

DataMites: Data Analytics Training in France

Ashok Veda and Faculty Excellence:

At the helm of DataMites is Ashok Veda, a distinguished leader with over 19 years of experience in Data Analytics and AI. Serving as the Founder & CEO at Rubixe™, his expertise enriches the educational experience, ensuring top-tier learning.

Comprehensive Course Curriculum:

Our Data Analytics Courses in France features a no-code program with an optional Python module, offering a 6-month duration with 20 hours of learning per week, totaling over 200 learning hours. The course culminates in the prestigious IABAC® Certification, globally recognized for proficiency.

Practical Learning and Internship Opportunities:

Immerse yourself in real-world applications through 5+ capstone projects and a client/live project. Our program includes a real-time internship opportunity, providing hands-on experience and enhancing practical skills.

Career Support and Exclusive Learning Community:

Benefit from end-to-end job support, personalized resume crafting, data analytics interview preparation, and job references. Join our exclusive learning community for networking, collaboration, and ongoing support.

Affordable Pricing and Scholarships:

Embark on this transformative journey with affordable pricing, with data analytics course fee in France ranging from FRF 2,584 to FRF 7,947. Explore scholarship opportunities to make quality education accessible to all aspiring Data Analysts. DataMites is your gateway to a successful career in data analytics.

France's data analytics industry thrives as a key player in global technological advancements, contributing significantly to informed decision-making across various sectors. With a focus on innovation and strategic insights, the industry positions itself as a crucial element in shaping the nation's digital landscape.

Data Analysts in France enjoy lucrative prospects, with an average salary of €40,525. According to Payscale, this substantial remuneration reflects the industry's recognition of the pivotal role Data Analysts play in unraveling insights, driving innovation, and contributing to the nation's digital success. In a landscape marked by high demand and specialized skills, Data Analysts stand as highly valued professionals, commanding competitive salaries in the vibrant French analytics arena.

Elevate your career in France with DataMites, where we not only lead in Data Analytics but also offer an array of courses in Artificial Intelligence, Tableau, Python, Machine Learning, Data Engineering, Data Science, and more. Under the guidance of industry expert Ashok Veda, our programs provide a solid foundation for career growth. Join DataMites to acquire expertise, engage with a vibrant learning community, and set yourself on the path to success in France's dynamic technology and analytics landscape.

ABOUT DATAMITES DATA ANALYST COURSE IN FRANCE

Data analytics entails systematically analyzing raw data to derive meaningful insights, patterns, and trends, utilizing various techniques and tools to inform decision-making processes.

Proficiency in programming languages like Python and R, along with statistical analysis, data cleaning, and visualization expertise, is crucial for those entering the field of data analytics. Strong critical thinking and communication skills are also essential.

Data visualization enriches data analytics by presenting intricate information visually, facilitating easier comprehension and communication of insights through graphs, charts, and dashboards.

Key job roles in data analytics encompass data analyst, business intelligence analyst, data scientist, and machine learning engineer. Each role specializes in different facets of data analysis, including descriptive analytics, predictive modeling, and data engineering.

Data analysis primarily involves extracting insights from existing datasets using descriptive and diagnostic analytics techniques. Conversely, data science encompasses a broader range of methodologies, including predictive modeling and machine learning, to derive insights and build predictive models from data.

Data analytics revolves around analyzing existing datasets to extract insights, often employing descriptive and diagnostic analytics. On the other hand, data science encompasses a more comprehensive approach, incorporating predictive modeling and machine learning techniques to derive insights and develop predictive models from data.

Data analysts typically engage in collecting, processing, and analyzing data to extract actionable insights. They organize datasets, identify trends, generate reports, and contribute to data-informed decision-making within organizations.

Data analytics involves analyzing existing datasets using descriptive and diagnostic analytics to extract insights. In contrast, data science encompasses a wider array of methodologies, including predictive modeling and machine learning, to derive insights, make predictions, and build models from data.

Data analytics involves analyzing datasets to extract insights using descriptive and diagnostic analytics techniques. Conversely, data science encompasses a broader set of methodologies, including predictive modeling and machine learning, to derive insights, develop predictive models, and make data-driven decisions.

Data analytics finds applications across industries. For instance, marketers leverage customer data for targeted campaigns, while healthcare utilizes analytics for patient care optimization through predictive modeling and trend analysis.

Technological progress, notably in AI and machine learning, shapes the future of data analytics by enabling automation, advanced algorithms, and real-time decision-making, revolutionizing analysis across industries.

Data analysis primarily focuses on examining existing datasets to extract insights through descriptive and diagnostic analytics methods. In contrast, data science encompasses a broader range of techniques, including predictive modeling and machine learning, to derive insights and create predictive models based on data.

Payscale data reveals that Data Analysts in France have promising earning potential, boasting an average annual salary of €40,525.

Internships offer practical experience, allowing aspiring analysts to apply theoretical knowledge in real-world scenarios, bridging the gap between academia and industry.

In marketing, data analytics analyzes customer behavior, preferences, and demographics to optimize advertising strategies, personalize campaigns, and measure effectiveness, facilitating data-driven decision-making for targeted and efficient marketing efforts.

Coding is vital in data analytics, notably with Python and R. Proficiency in coding enhances data manipulation and analysis, though different roles may require varying levels of coding expertise.

While full proficiency varies, with a structured plan and consistent effort, individuals can establish a solid foundation in data analytics within six months.

DataMites stands out for its top-notch data analytics courses in France, emphasizing practical, industry-aligned skills for success in the field.

Retail leverages data analytics for inventory management, demand forecasting, and customer behavior analysis, optimizing pricing, personalization, and supply chain efficiency.

SQL is a specialized language for managing databases, focusing on tasks like querying and data manipulation, setting it apart from the broader spectrum of data analytics.

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FAQ’S OF DATA ANALYST TRAINING IN FRANCE

DataMites' Certified Data Analyst Training in France targets beginners and intermediate learners in data analytics. It emphasizes career readiness, covering data analysis, data science, statistics, visual analytics, data modeling, and predictive modeling, ideal for individuals aspiring to roles in the data analytics field.

DataMites' Data Analyst Course in France is a 6-month program, with students committing 20 hours weekly to learning. Boasting over 200 learning hours, the curriculum ensures participants develop proficient data analysis skills crucial for career advancement.

The certified data analyst training in France by DataMites encompasses a wide range of tools essential for data analysis, including Advanced Excel, MySQL, MongoDB, Git, GitHub, Atlassian BitBucket, Hadoop, Apache Pyspark, Anaconda, Google Collab, Numpy, Pandas, Tableau, and Power BI.

Enrolling in DataMites' Certified Data Analyst Course in France offers unparalleled benefits. These include flexible learning options, a curriculum tailored to industry needs, renowned instructors, access to an exclusive Practice Lab, and a collaborative learning atmosphere. Moreover, students receive lifetime access, exposure to various projects, and dedicated placement support, making DataMites the go-to destination for aspiring data analysts.

DataMites' Data Analytics Course fee in France spans from FRF 2,584 to FRF 7,947, accommodating a wide range of budgets and requirements. This pricing flexibility allows learners to select a package that best fits their educational goals and financial capabilities, ensuring inclusivity and affordability.

Certainly! DataMites provides comprehensive support to aid your understanding of data analytics course in France. With our expert assistance, you'll receive personalized guidance and resources tailored to your learning needs, empowering you to grasp complex concepts effectively.

The Certified Data Analyst Training in France encompasses Data Analysis Fundamentals, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, SQL and MongoDB Database Management, Git Version Control, Big Data Foundations, Python Fundamentals, and Certified Business Intelligence (BI) Analyst modules.

In France, the Certified Data Analyst Course emphasizes advanced analytics and business insights. It's a No-Code program designed for data analysts and managers to excel in advanced analytics, even without prior programming knowledge. Optional Python training is available. The curriculum is regularly updated to meet industry demands, ensuring a streamlined learning experience for effective skill development.

The trainers for DataMites' Certified Data Analyst Course in France include Ashok Veda and elite Lead Mentors known for their proficiency in Data Science and AI.

With the Flexi Pass option for the Certified Data Analyst Course in France, participants can customize their learning experience, adjusting study hours and duration to suit their individual needs and preferences.

Aspirants completing the Certified Data Analyst Course in France will be awarded IABAC Certification, signifying their mastery in data analytics and validating their skills for prospective employers.

DataMites' Certified Data Analyst Course in France adopts a case study-based methodology, immersing participants in real-life scenarios to cultivate analytical skills and problem-solving abilities effectively.

Participants in France can access DataMites' data analytics courses through either Online Data Analytics Training in France or Self-Paced Training, offering flexibility and autonomy in their learning approach to accommodate diverse preferences and schedules effectively.

Absolutely, DataMites offers internships alongside the Certified Data Analyst Course in France. Partnering with leading Data Science companies, these internships allow learners to implement their learning in real-world scenarios. With the support of DataMites experts and mentors, participants gain valuable industry experience, enriching their educational journey.

Missing a data analytics session in France isn't a setback with DataMites. You can access recorded sessions and supplementary materials to catch up on missed content. Instructors and online communities are also available for assistance and clarification on any concepts you may have missed.

Participants are reminded to bring a valid photo ID such as a national ID card or driver's license to data analytics training sessions. This is required for receiving your participation certificate and scheduling certification exams smoothly. Thank you for your cooperation.

Structured data analytics career mentoring sessions in France offer tailored guidance and support to participants. Featuring personalized coaching from seasoned mentors, these sessions include career assessments, goal setting strategies, skill development plans, networking opportunities, and ongoing support to help individuals succeed in their chosen career paths.

DataMites' Certified Data Analyst Course is highly valued in France for its non-coding approach, facilitating accessibility for non-technical aspirants. The 3-month internship experience in an AI Company, along with an experience certificate and prestigious IABAC Certification, underscores its significance, ensuring participants receive top-tier training from expert faculty.

Indeed, DataMites provides live projects as part of the data analyst course in France. With 5+ capstone projects and 1 client/live project, participants gain hands-on experience in data analytics, developing practical skills and insights crucial for success in the field.

Participants enrolling in DataMites' Certified Data Analytics Course in France can conveniently pay through cash, debit card, check, credit card (Visa, Mastercard, American Express), EMI, PayPal, or net banking, providing multiple options to suit individual preferences and requirements.

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.

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