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 discipline that involves extracting valuable insights and knowledge from extensive sets of structured and unstructured data. It employs various techniques, algorithms, and systems to analyze, interpret, and present data.
The Data Science process operates by collecting, cleaning, and analyzing data to derive meaningful patterns and trends. It often involves the use of statistical models, machine learning algorithms, and data visualization techniques to make informed decisions.
Data Science finds applications in predictive analytics, fraud detection, recommendation systems, sentiment analysis, and optimizing business processes across various industries.
Key components of a Data Science pipeline include data collection, data cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment.
Commonly used programming languages in Data Science include Python and R. They are popular for their extensive libraries and frameworks that facilitate data manipulation, analysis, and machine learning.
Machine learning is integral to Data Science, enabling systems to learn patterns from data and make predictions or decisions without explicit programming. It enhances the ability to extract valuable insights from complex datasets.
Big Data is closely linked to Data Science as it involves handling and analyzing massive datasets that traditional data processing tools may struggle with. Data Science techniques and algorithms are often applied to extract meaningful information from Big Data.
Data Science is applied in industries such as healthcare, finance, marketing, and manufacturing to optimize operations, improve decision-making, and enhance overall business performance.
While Data Science encompasses a broader range of activities, including data cleaning, exploration, and visualization, machine learning specifically focuses on developing algorithms that enable systems to learn patterns and make predictions.
Individuals from diverse backgrounds, including IT professionals, statisticians, analysts, and business professionals, are eligible to pursue Data Science certification courses. A basic understanding of statistics and programming is beneficial for learning Data Science.
The data science job market in Malé in 2024 is experiencing growth, with a rising demand for skilled professionals.
Recognized as a premier option for data science training, the Certified Data Scientist Course in Malé covers essential topics such as machine learning and data analysis.
Data science internships are highly valuable in Malé, offering practical experience and contributing to increased employability.
Certainly, an entry-level individual can undertake a data science course and land a job in Malé, as companies are willing to hire skilled beginners.
No, possessing a postgraduate degree is not obligatory for enrolling in data science training courses in Malé; many programs accept candidates with relevant undergraduate backgrounds.
Businesses in Malé harness data science for growth by improving decision-making, optimizing operations, and enhancing customer experiences.
In finance, data science is applied to risk management, fraud detection, and predictive analytics.
Data science contributes to e-commerce by powering recommendation systems, personalized marketing, and forecasting demand.
In cybersecurity, data science plays a pivotal role in detecting anomalies, identifying patterns, and improving threat detection and prevention measures.
In manufacturing and supply chain management, data science optimizes production processes, predicts demand, and enhances logistics efficiency.
The Datamites™ Certified Data Scientist course is designed to cover key aspects of data science, including programming, statistics, machine learning, and business knowledge. It focuses on Python as the primary programming language, with the inclusion of R for professionals familiar with that language. The curriculum is comprehensive, ensuring a strong foundation, and successful completion, coupled with the IABAC™ certificate, positions individuals as proficient data science professionals ready for industry challenges.
While a statistical background can be advantageous, it's not always a prerequisite for a data science career in Malé. Proficiency in relevant tools, programming languages, and practical problem-solving skills is often prioritized.
DataMites in Malé provides a range of data science certifications, including a Diploma in Data Science, Certified Data Scientist, Data Science for Managers, Data Science Associate, Statistics for Data Science, Python for Data Science, and specialized certifications in various domains like Marketing, Operations, Finance, and HR.
Individuals new to the field in Malé can consider courses such as Certified Data Scientist, Data Science Foundation, and Diploma in Data Science for foundational training in data science.
DataMites in Malé offers a variety of courses tailored for professionals aiming to boost their expertise, including Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and specialized certifications in Operations, Marketing, HR, and Finance.
The data science course in Malé has a duration of 8 months.
Career mentoring sessions at DataMites are interactive, providing personalized guidance on resume building, interview preparation, and career strategies. These sessions offer valuable insights to enhance the professional journey of participants in the field of data science.
Upon successful completion, participants receive the prestigious IABAC Certification from DataMites, internationally recognized as proof of proficiency in data science concepts and practical applications.
To excel in data science, a solid foundation in mathematics, statistics, and programming is crucial. Developing strong analytical skills, proficiency in languages like Python or R, and hands-on experience with tools like Hadoop or SQL databases is recommended.
Opting for online data science training in Malé provides flexibility, accessibility, a comprehensive curriculum aligned with industry needs, industry-relevant content, experienced instructors, interactive learning, and the ability to learn at one's own pace.
The data science training fee in Malé ranges from MVR 7,382 to MVR 20,401, depending on the specific program.
Yes, DataMites offers a Data Scientist Course in Malé that includes practical learning with over 10 capstone projects and a dedicated client/live project, providing hands-on experience and real-world applications.
Trainers at DataMites are selected based on certifications, extensive industry experience, and expertise in the subject matter.
DataMites offers flexible learning methods, including Live Online sessions and self-study, to cater to participants' preferences.
The FLEXI-PASS option in DataMites' Certified Data Scientist Course allows participants to join multiple batches, enabling them to review topics, address doubts, and solidify comprehension across various sessions for a comprehensive understanding of the course content.
Certainly, upon the successful completion of DataMites' Data Science Course, participants can request a Certificate of Completion through the online portal. This certification serves as validation of their proficiency in data science, bolstering their credibility in the competitive job market.
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.
In case of a missed session in the DataMites Certified Data Scientist Course in Malé, participants usually have the option to access recorded sessions or attend support sessions to make up for missed content and clarify doubts.
Yes, potential participants at DataMites can attend a demo class before making any payment for the Certified Data Scientist Course in Malé to assess the teaching style, course content, and overall structure.
Yes, DataMites incorporates internships into its certified data scientist course in Malé, providing a unique learning experience that combines theoretical knowledge with practical industry exposure, enhancing skills and job opportunities in the dynamic field of data science.
Upon successful completion of the Data Science training, you will be granted an internationally recognized IABAC® certification. This certification confirms your proficiency in the field and elevates your employability on a global level.
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.