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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 a multidisciplinary field focused on extracting insights and knowledge from data. It functions by employing statistical methods, machine learning algorithms, and analytical techniques to analyze, interpret, and draw meaningful conclusions from complex datasets.
The Data Science process involves data collection, cleaning, analysis, and interpretation. Its practical implications include informed decision-making, trend predictions, pattern recognition, and the optimization of processes across various industries.
Real-world applications of Data Science span healthcare, finance, marketing, and more. A Data Science pipeline comprises data collection, cleaning, exploration, feature engineering, modeling, evaluation, and deployment.
Big Data, characterized by vast and complex datasets, is intrinsically linked to Data Science. Data Science techniques and tools are essential for processing, analyzing, and deriving meaningful insights from Big Data.
Data Science in e-commerce enhances customer experiences through recommendation systems. It analyzes user behavior, preferences, and purchase history to provide personalized product recommendations, thereby boosting engagement and sales.
Data Science strengthens cybersecurity by identifying patterns indicative of cyber threats, predicting risks, and implementing proactive measures. It aids in anomaly detection, threat intelligence, and the development of robust security protocols.
Data Science finds applications in diverse industries, from healthcare for personalized treatments to finance for risk analysis. It optimizes processes, informs decision-making, and addresses industry-specific challenges, showcasing its adaptability and impact across various sectors.
Data Science encompasses a broader scope, involving data collection, analysis, and interpretation. Machine learning is a subset of Data Science, focusing specifically on developing algorithms that enable systems to learn patterns and make predictions from data.
Individuals with backgrounds in mathematics, statistics, computer science, or related fields qualify for Data Science certification courses. Proficiency in programming languages like Python is beneficial.
Crafting a data science portfolio involves selecting diverse projects, showcasing coding skills, incorporating visualizations, and providing detailed explanations of methodologies and outcomes.
Yes, transitioning from a non-coding background to Data Science is possible. Learning programming languages, statistics, and machine learning is crucial to build a solid foundation.
While a bachelor's degree in computer science, statistics, or related fields is common, some enter with degrees in physics, engineering, or economics. Advanced degrees (master's or Ph.D.) enhance prospects.
Essential skills for a Data Scientist include proficiency in programming languages, statistical analysis, machine learning, data visualization, and strong communication and problem-solving abilities.
Emerging trends in Data Science include the rise of automated machine learning, increased focus on ethical considerations, and the integration of artificial intelligence in data analysis and decision-making processes. Continual learning and adaptation to new tools and technologies are also crucial in this evolving field.
Kickstarting a data science career in Algeria involves acquiring foundational knowledge in statistics, programming, and machine learning. Engaging in practical projects, building a strong portfolio, and networking within the local data science community are essential steps. Exploring online courses and seeking mentorship can provide additional support.
As of 2024, the data science job market in Algeria is promising, with increasing demand for skilled professionals. Industries like finance, healthcare, and telecommunications are actively seeking data scientists to leverage insights for strategic decision-making.
For top-notch data science education in Algeria, the Certified Data Scientist Course in Algeria is a standout option, providing expertise in machine learning and data analysis.
Data science internships in Algeria are highly valuable as they provide practical experience, exposure to real-world projects, and opportunities to network. Internships enhance skills and increase employability in the competitive job market.
In Algeria, professionals in the field of Data Science can expect a lucrative average annual salary of DZD 80,000, based on Glassdoor data. This figure provides valuable insights into the earning potential for Data Scientists in Algeria, reflecting the competitive compensation offered in the local job market.
Yes, newcomers can undertake data science courses in Algeria and secure jobs. Entry-level positions such as data analyst or junior data scientist roles are accessible with the right skills, portfolio, and determination. Engaging in local meetups and networking events can also enhance job prospects.
The DataMites Certified Data Scientist Course in Algeria is globally recognized as the most comprehensive and job-oriented program in Data Science and Machine Learning. It undergoes frequent updates to meet industry demands, ensuring that the learning process is finely tuned for a structured and effective educational journey.
For beginners entering the field in Algeria, accessible training options include the Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science courses.
Certainly, DataMites in Algeria offers specialized courses for working professionals seeking knowledge augmentation, 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.
DataMites offers data scientist courses in Algeria with durations spanning from 1 to 8 months, depending on the course level.
No prior requirements are needed for the Certified Data Scientist Training in Algeria, catering to both beginners and intermediate learners in the domain of data science.
DataMites' online training enables flexible, self-paced learning, accommodating diverse lifestyles. Accessible to anyone with an internet connection, it ensures quality education, breaking geographical barriers. The comprehensive curriculum covers essential data science concepts and practical applications, tailored to meet industry demands. Learners receive expert guidance from seasoned instructors, navigating the complexities of data science for a rich learning experience aligned with job requirements.
Certainly, the fee structure for DataMites' data science training in Algeria spans from DZD 71,024 to DZD 177,581. This competitive pricing allows individuals to access quality education and acquire valuable skills in the realm of data science at affordable rates.
The training sessions at DataMites are led by accomplished mentors and faculty members with real-world experience from prominent companies and prestigious institutes like IIMs.
Certainly, participants are required to bring a valid photo ID proof, like a national ID card or driver's license, to collect their participation certificate and schedule the certification exam, if needed.
Participants in Algeria who miss a data science training session with DataMites can access recorded sessions and supplementary materials, ensuring they can catch up on the content at their own pace.
Yes, DataMites provides an opportunity for a demo class in Algeria, allowing participants to experience the structure and content of the data science training before committing to the fee.
Yes, DataMites offers data science courses with internship opportunities in Algeria, providing participants with hands-on experience and practical exposure in real-world scenarios.
Specifically curated for managers, the "Data Science for Managers" course at DataMites is tailored to equip leaders with essential skills, facilitating the seamless integration of data science into their decision-making processes.
Yes, there is an option in Algeria for participants to attend help sessions, providing additional support for a better grasp of specific data science topics, promoting thorough understanding and knowledge retention.
Yes, participants in Algeria undertaking DataMites' Data Scientist Course engage in 10+ capstone projects and a live client project. This practical component enhances their proficiency, allowing them to apply theoretical knowledge to real-world situations.
Yes, DataMites issues a Data Science Course Completion Certificate upon successfully finishing the program. Participants need to attend the training, complete assignments, and pass assessments. Certificates can be obtained by fulfilling these requirements.
The Flexi-Pass at DataMites provides flexibility for participants to attend missed sessions. It offers access to recorded sessions, ensuring learners can catch up at their convenience, fostering a more adaptable and personalized learning experience.
DataMites' career mentoring sessions are structured to guide participants through various career aspects. They cover resume building, interview preparation, and personalized career advice, aiding individuals in their journey to secure relevant positions in the data science field.
DataMites in Algeria adapts its training methods to suit diverse participant requirements. Live online training promotes real-time interaction, creating an immersive learning environment. Alternatively, participants can embrace self-paced training, accessing recorded sessions at their convenience. This flexibility supports personalized learning, accommodating varying schedules, and optimizing overall outcomes.
Successful completion of DataMites' Data Science Training in Algeria grants participants the prestigious IABAC Certification. Recognized globally, this certification validates their mastery of data science concepts and practical applications, enhancing their professional credibility within the data science domain.
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.