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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 field has an expansive scope, covering machine learning, statistics, and data analysis to extract insights and inform decision-making processes.
Big Data and Data Science intersect in handling and analyzing large datasets, with Big Data emphasizing tools and technologies for managing massive data volumes.
While coding experience is advantageous, individuals without it can still pursue a Data Science career using no-code/low-code platforms.
Educational qualifications for Data Science roles usually include a bachelor's or master's degree in related fields like computer science, statistics, or mathematics.
Aspiring Data Scientists should possess skills in programming (e.g., Python), statistics, machine learning, data visualization, and strong problem-solving abilities.
To create an effective portfolio, individuals should showcase real-world projects, highlight problem-solving skills, and demonstrate proficiency in relevant tools and techniques.
Proficiency in Python is often considered a prerequisite for Data Science roles due to its widespread use in data analysis, machine learning, and building data pipelines.
The typical career path for a Data Scientist in Uzbekistan may involve roles such as Data Analyst, Junior Data Scientist, Senior Data Scientist, and potential progression to managerial positions.
Enrollment in Data Science Certification Courses is generally open to individuals with a background in mathematics, statistics, computer science, or related fields.
Initial steps for individuals entering the Data Science field in Uzbekistan include gaining foundational knowledge, acquiring relevant technical skills, and networking with local professionals and organizations.
Compensation for Data Scientists in Uzbekistan varies but is influenced by experience, skills, and industry, with an average salary range of UZS 25,22,500 annually.
Crafting an impactful portfolio for a Data Science position involves showcasing diverse projects, highlighting technical skills, and providing clear explanations of methodologies and outcomes.
High demand for Data Scientists is currently observed in tech hubs like Silicon Valley, financial centers, and healthcare sectors globally.
Emerging trends in Data Science include explainable AI, automated machine learning, and an increased focus on ethical considerations in AI applications.
A postgraduate degree is not always a prerequisite for data science training in Uzbekistan; many programs accept candidates with relevant experience and skills.
The Data Science workflow includes data collection, cleaning, exploration, modeling, validation, and deployment, with iterative steps for continuous improvement.
Data Science in Uzbekistan contributes to business growth through improved decision-making, customer insights, and optimized operations, enhancing competitiveness.
The Certified Data Scientist Course is a top-tier option for data science training in Uzbekistan, covering essential topics such as machine learning and data analysis.
Industries utilizing Data Science range from finance and healthcare to e-commerce and telecommunications, with applications in predictive analytics, fraud detection, and personalized marketing.
Data Science focuses on extracting insights from data, while Machine Learning is a subset that involves training models to make predictions or decisions based on data.
The DataMites Certified Data Scientist Course in Uzbekistan is a globally recognized, comprehensive program in Data Science and Machine Learning, regularly updated to meet industry demands. It provides a systematic learning experience for efficient and focused learning.
Certainly, DataMites in Uzbekistan offers various data science certifications, including 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 areas like Marketing, Operations, Finance, and HR.
For beginners in Uzbekistan entering the field of data science, entry-level training options include courses such as Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science.
Yes, DataMites in Uzbekistan provides specialized courses for working professionals, including 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 Uzbekistan varies from 1 month to 8 months, depending on the specific level of the course.
Enrollment in the Certified Data Scientist Training in Uzbekistan is open to beginners and intermediate learners in the field of data science, with no prerequisites required.
Online data science training in Uzbekistan from DataMites offers benefits such as adaptability, accessibility, a comprehensive curriculum, industry-relevant content, expert instructors, and interactive learning experiences.
DataMites' data science training in Uzbekistan has a fee structure ranging from UZS 5,922,198 to UZS 16,365,828 ensuring affordable options for individuals to access quality education in the field of data science.
Instructors at DataMites are selected based on certifications, extensive industry experience, and mastery of the subject matter 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.
In the DataMites Certified Data Scientist Course in Uzbekistan, participants have the flexibility to access recorded sessions or participate in support sessions if they miss a class. This ensures that learners can review missed content, clarify uncertainties, and stay aligned with the course curriculum.
Certainly, prospective participants in the Certified Data Scientist Course in Uzbekistan have the opportunity to attend a demo class before making any payment. This allows them to assess teaching style, course content, and overall structure, empowering them to make an informed enrollment decision.
DataMites incorporates internships into its certified data scientist course in Uzbekistan, offering a unique learning experience that combines theoretical knowledge with practical industry exposure. This enhances skills and job opportunities in the dynamic field of data science.
Designed exclusively for managers and leaders, the "Data Science for Managers" course at DataMites is crafted to meet their specific requirements. This course equips them with essential skills to seamlessly integrate data science into decision-making processes, facilitating well-informed and strategic choices.
Certainly, individuals in Uzbekistan participating in the program have the choice to attend help sessions, providing a valuable opportunity for a more in-depth understanding of specific data science topics. This ensures a thorough learning experience and addresses individual queries effectively.
Indeed, DataMites offers a Data Scientist Course in Uzbekistan that includes hands-on learning with over 10 capstone projects and a dedicated client/live project. This practical experience enhances participants' skills by providing real-world applications and industry-relevant exposure.
Certainly, DataMites provides a Data Science Course Completion Certificate. Upon successful completion of the course, participants can request the certificate through the online portal. This certificate validates their proficiency in data science, enhancing credibility in the job market.
The FLEXI-PASS feature in DataMites' Certified Data Scientist Course allows participants to enroll in multiple batches, providing flexibility to revisit topics, address uncertainties, and deepen comprehension through various sessions. This ensures a comprehensive and personalized learning experience.
DataMites' career mentoring sessions adopt an interactive format, offering personalized guidance on resume building, interview preparation, and career strategies. These sessions provide valuable insights and effective strategies to elevate participants' professional journey in the field of data science.
Online Training: DataMites in Uzbekistan provides live online training, facilitating real-time interaction with instructors and creating an engaging and interactive learning environment for participants.
Self-Paced Training: Participants can access recorded sessions at their convenience, allowing for a personalized learning pace and accommodating diverse schedules to optimize learning outcomes.
Upon successful completion of the Data Science training, you will be awarded an internationally recognized IABAC® certification, validating your proficiency in the field and enhancing your global employability.
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.