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 encompasses the field dedicated to extracting valuable insights and knowledge from extensive sets of structured and unstructured data. It relies on various methods, algorithms, and systems to analyze, interpret, and present information.
The process of Data Science involves the collection, cleansing, and analysis of data to uncover meaningful patterns and trends. Statistical models, machine learning algorithms, and data visualization techniques are commonly employed to make well-informed decisions.
Data Science finds practical applications in predictive analytics, fraud detection, recommendation systems, sentiment analysis, and the optimization of business processes across diverse industries.
Critical components of a Data Science pipeline include data collection, data cleaning, exploratory data analysis (EDA), feature engineering, model training, model evaluation, and deployment.
Data Science commonly relies on programming languages such as Python and R. These languages are well-regarded for their extensive libraries and frameworks that facilitate tasks like data manipulation, analysis, and machine learning.
Machine learning holds a pivotal role in Data Science by enabling systems to learn patterns from data and make predictions or decisions without explicit programming. This capability enhances the extraction of valuable insights from intricate datasets.
Big Data shares a close relationship with Data Science as it involves managing and analyzing vast datasets that conventional tools may struggle to handle. Data Science methodologies and algorithms are frequently applied to extract meaningful insights from the challenges posed by Big Data.
The versatility of Data Science is evident across industries such as healthcare, finance, marketing, and manufacturing. Its applications range from optimizing operational processes to elevating decision-making and overall business performance.
While Data Science encompasses a broader spectrum of activities, including data cleaning, exploration, and visualization, machine learning specifically concentrates on developing algorithms that empower systems to learn patterns and make predictions.
Certification courses in Data Science are open to individuals from various backgrounds, including IT professionals, statisticians, analysts, and business experts. A foundational understanding of statistics and programming proves beneficial for those embarking on the journey of learning Data Science.
In 2024, the data science job market in Cambodia is flourishing, witnessing a surge in demand for skilled professionals.
Engaging in data science internships is advantageous in Cambodia, providing practical experiences that enhance one's employability within the field.
According to a Glassdoor report, the salary for data scientists in Cambodia ranges from KHR 67,00,000 per year according to a Glassdoor.
Certainly, individuals without prior experience can enroll in data science courses and secure jobs in Cambodia, as companies are increasingly willing to hire skilled beginners.
Enrolling in data science training courses in Cambodia does not mandate a postgraduate degree; many programs accept candidates with relevant undergraduate backgrounds.
Businesses in Cambodia leverage data science for growth by enhancing decision-making processes, optimizing operations, and elevating overall customer experiences.
In the finance sector, data science is applied to areas such as risk management, fraud detection, and predictive analytics.
Data science contributes to e-commerce by powering recommendation systems, enabling personalized marketing strategies, and facilitating accurate demand forecasting.
In the domain of cybersecurity, data science plays a critical role in identifying anomalies, discerning patterns, and strengthening overall threat detection and prevention measures.
In manufacturing and supply chain management, data science is instrumental in optimizing production processes, forecasting demand, and improving overall logistics efficiency.
Datamites™ Certified Data Scientist course encompasses programming, statistics, machine learning, and business knowledge. With a focus on Python as the primary language (with the optional use of R), the course offers a solid foundation in data science. Completion leads to an IABAC™ certificate, preparing individuals for successful careers as proficient data science professionals.
While a statistical background can be advantageous, it is not always mandatory for a data science career in Cambodia. Proficiency in relevant tools, programming languages, and practical problem-solving skills often take precedence in the field.
DataMites provides a range of certifications in Cambodia, including the 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 Operations, Marketing, HR, Finance, among others.
For beginners in Cambodia, options include courses like Certified Data Scientist, Data Science Foundation, and Diploma in Data Science, offering foundational knowledge to kickstart a career in data science.
In Cambodia, DataMites offers specialized courses tailored for professionals, covering 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 data science course in Cambodia provided by DataMites has a duration of 8 months, ensuring a comprehensive and in-depth learning experience.
Career mentoring sessions at DataMites are interactive, providing personalized guidance on resume building, interview preparation, and career strategies. Participants receive valuable insights and tactics to enhance their professional journey in the field of data science.
Upon completing the training, participants receive the prestigious IABAC Certification from DataMites. This globally recognized certification validates their proficiency in data science concepts and applications, bolstering credibility in the industry.
To excel in Certified Data Scientist Training in Cambodia, a strong foundation in mathematics, statistics, and programming is essential. Candidates should possess analytical skills, proficiency in either Python or R, and hands-on experience with extensive datasets and tools like Hadoop or SQL databases.
Online data science training in Cambodia from DataMites offers advantages such as self-paced learning, accessibility from any location, a curriculum aligned with industry requirements, industry-relevant content, guidance from experienced instructors, and engaging learning experiences through interactive features.
The fee structure for data science training in Cambodia with DataMites ranges from KHR 2,156,268 to KHR 5,391,285
Certainly, DataMites' Data Scientist Course in Cambodia includes hands-on learning with over 10 capstone projects, including a dedicated client/live project for real-world application and exposure to industry practices.
Instructors at DataMites are selected based on certifications, extensive industry experience, and demonstrated mastery of the subject matter. The data science training sessions are conducted by these qualified and experienced professionals.
DataMites offers flexible learning options, including Live Online sessions and self-study, allowing participants to choose the method that best suits their preferences and learning styles.
The Flexi-Pass option in DataMites' Certified Data Scientist Course allows participants to join multiple batches for a comprehensive learning experience. This enables them to revisit topics, clarify doubts, and enhance their understanding across various sessions, contributing to a more thorough grasp of the material.
Yes, upon completion of the Data Science Course in Cambodia, DataMites issues a Certificate of Completion, validating participants' proficiency in data science.
Participants need 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 if necessary.
In the event of a missed session in the DataMites Certified Data Scientist Course in Cambodia, participants can access recorded sessions or participate in support sessions to catch up on missed content and address any doubts.
Certainly, prospective participants at DataMites have the option to attend a demo class before enrolling in the Certified Data Scientist Course in Cambodia. This allows them to assess the teaching style, course content, and overall structure before making a commitment.
DataMites integrates internships into its certified data scientist course in Cambodia, providing a unique learning experience that combines theoretical knowledge with practical industry exposure.
Upon successfully completing the Data Science training, participants receive an internationally recognized IABAC® certification. This certification validates their expertise in the field and enhances their employability on a global scale.
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.