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 practically applied in enhancing decision-making, predicting trends, optimizing processes, and solving complex problems across various industries.
Key stages in a Data Science workflow encompass problem definition, data collection, data cleaning, exploratory data analysis, feature engineering, modeling, evaluation, and deployment.
Big Data and Data Science are intertwined, with Data Science utilizing advanced analytics to extract meaningful insights from large and intricate datasets known as Big Data.
Data Science influences e-commerce by tailoring recommendations, improving customer experience, and optimizing pricing strategies to boost sales and satisfaction.
Data Science enhances cybersecurity through anomaly detection, pattern recognition, and predictive analytics, identifying and preventing potential security threats.
Data Science finds application in diverse industries such as healthcare, finance, marketing, and manufacturing, aiding in informed decision-making and process optimization.
Distinguishing Data Science from machine learning: Data Science covers a broader spectrum of techniques for extracting insights from data, while machine learning specifically focuses on developing algorithms for predictive modeling.
Eligible candidates for Data Science certification courses include individuals with a background in statistics, mathematics, computer science, or related fields seeking expertise in data analysis.
The term Data Science encompasses extracting knowledge and insights from structured and unstructured data using scientific methods, processes, algorithms, and systems.
The functioning mechanism of Data Science involves collecting, processing, analyzing, and interpreting data to extract valuable insights and support informed decision-making across various domains.
Construct a data science portfolio by completing projects, showcasing coding skills, and highlighting problem-solving abilities.
Transitioning from a non-coding background to data science is feasible by learning programming languages like Python or R, gaining statistical knowledge, and building a robust portfolio.
Educational qualifications for data science typically include a degree in a related field (e.g., statistics, computer science, or mathematics) and proficiency in relevant programming languages.
Vital skills for aspiring data scientists include programming, statistical analysis, machine learning, data visualization, and domain-specific knowledge.
Initial steps in Bhutan involve acquiring key data science skills, engaging in online courses or bootcamps, and networking with local professionals.
The job market outlook for data science in Bhutan in 2024 may vary, but there is a general global increase in demand for skilled data scientists.
The Certified Data Scientist Course in Bhutan is widely recognized for its excellence in data science training, covering essential topics such as machine learning and data analysis.
Internships in Bhutan offer significant value in the field of data science, providing practical experience, fostering networking opportunities, and enhancing overall employability.
Data Science salaries in Bhutan are competitive, with a reported range starting from BTN 86,000 per year according to the Glassdoor report.
Certainly, individuals without prior experience can undertake a data science course in Bhutan and secure a job by building a strong portfolio showcasing acquired skills and knowledge. Practical projects and networking can significantly enhance employability.
The DataMites Certified Data Scientist Course in Bhutan stands out as a premier, comprehensive, and career-oriented program in the realm of Data Science and Machine Learning on a global scale. It undergoes regular updates to align with industry requirements, ensuring its ongoing relevance. This meticulously designed course aims to provide a structured learning journey, allowing participants to acquire knowledge systematically and with a distinct emphasis.
For those new to the field in Bhutan, introductory training options include courses such as Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science.
Certainly, DataMites in Bhutan offers specialized courses designed for professionals seeking to enhance their skills. These include 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 Bhutan varies, ranging from 1 month to 8 months, depending on the specific level of the course.
No prerequisites are required for enrolling in the Certified Data Scientist Training in Bhutan, making it accessible to beginners and intermediate learners in the field of data science.
Online data science training in Bhutan from DataMites provides flexibility, allowing participants to learn at their own pace and overcome geographical barriers. The comprehensive curriculum is aligned with industry needs, and expert instructors ensure an interactive learning experience.
DataMites' data science training fees in Bhutan range from BTN 44,152 to BTN 110,394 providing affordable options for quality education in data science.
Instructors at DataMites are chosen based on certifications, extensive industry experience, and proven expertise in the subject matter, ensuring high-quality training sessions.
Participants in DataMites Certified Data Scientist Course in Bhutan are required to present a valid Photo ID Proof, such as a National ID card or Driving License, to obtain a Participation Certificate.
If a participant misses a session in the DataMites Certified Data Scientist Course in Bhutan, they usually have the option to access recorded sessions or participate in support sessions, ensuring they stay on track with the course.
Certainly, prospective participants can attend a demo class for the Certified Data Scientist Course in Bhutan at DataMites before making any payment, allowing them to assess the course structure and teaching style.
Yes, DataMites integrates internships into its certified data scientist course in Bhutan, providing practical industry exposure and enhancing participants' skills and job opportunities.
DataMites offers a "Data Science for Managers" course designed exclusively for managers and leaders, providing essential skills to seamlessly incorporate data science into decision-making processes.
Certainly, participants in Bhutan have the option to attend help sessions, offering a deeper understanding of specific data science topics and ensuring a comprehensive learning experience.
Indeed, DataMites' Data Scientist Course in Bhutan includes hands-on learning with over 10 capstone projects and a dedicated client/live project, providing practical industry exposure.
Upon successful completion of the Data Science Course, participants can request the certificate through the online portal, validating their proficiency in data science. Students will receive internationally recognized IABAC certification after completion of the data science course in Bhutan
The FLEXI-PASS feature in DataMites' Certified Data Scientist Course allows participants to enroll in multiple batches, providing flexibility to revisit topics and enhance their understanding for a comprehensive learning experience.
Career mentoring sessions at DataMites follow an interactive format, offering personalized guidance on resume building, interview preparation, and career strategies to enhance participants' professional journey in data science.
DataMites offers live online training and self-paced training, providing flexibility and personalized learning experiences for participants in Bhutan.
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.