Instructor Led Live Online
Self Learning + Live Mentoring
Customize Your Training
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 extracting insights from data through scientific methods. Its operational mechanism involves data collection, cleaning, analysis, and interpretation using statistical and machine learning techniques, contributing to informed decision-making.
Data Science functions by collecting and analyzing data to extract meaningful insights. Practical applications span diverse fields, including finance for risk assessment, healthcare for personalized treatments, and marketing for targeted campaigns.
Big Data is intertwined with Data Science as it involves processing vast datasets. Data Science enhances e-commerce through recommendation systems, analyzing user behavior to provide personalized suggestions, improving customer engagement and sales.
A Data Science pipeline comprises data collection, cleaning, exploration, feature engineering, modeling, evaluation, and deployment. Each stage contributes to systematic data analysis and extraction of valuable insights.
Data Science enhances cybersecurity by detecting anomalies, predicting threats, and implementing proactive measures. Across industries, it's employed for risk analysis, fraud detection, and process optimization, contributing to data-driven decision-making.
Data Science is a broader field, encompassing data analysis and interpretation, while machine learning is a subset focused on creating algorithms for systems to learn from data. Individuals with backgrounds in math, statistics, or computer science often qualify for Data Science certification courses.
Yes, individuals from non-coding backgrounds can transition to Data Science. Learning programming languages like Python, statistics, and machine learning is crucial. Educational prerequisites typically include a background in mathematics, statistics, or related fields.
Critical skills include programming, statistical analysis, machine learning, and effective communication. To craft an effective portfolio, showcase a variety of projects, demonstrate coding proficiency, incorporate clear visualizations, and articulate the impact and insights of each project.
Data Science is applied across industries for predictive modeling, process optimization, and decision-making. The distinction with machine learning lies in Data Science's broader scope, encompassing data analysis, interpretation, and decision-making.
Those with backgrounds in mathematics, statistics, computer science, or related fields qualify for Data Science certification courses. Proficiency in programming languages like Python is advantageous.
The process involves selecting diverse projects, showcasing coding skills, providing explanations, and incorporating impactful visualizations. Highlight real-world applications and outcomes, demonstrating problem-solving abilities.
Yes, it is feasible. Learning programming languages, statistics, and machine learning is essential. Building a strong foundation and gaining practical experience through projects can facilitate the transition.
While a bachelor's degree in computer science, statistics, or related fields is common, degrees in physics, engineering, or economics are also accepted. Advanced degrees (master's or Ph.D.) enhance career prospects.
Essential skills include proficiency in programming languages, statistical analysis, machine learning, data visualization, and strong communication. Problem-solving and domain-specific knowledge further enhance success in the dynamic field of Data Science.
Initiate a data science career in Algiers by acquiring foundational knowledge in statistics, programming, and machine learning. Engage in real-world projects, build a strong portfolio, and network within the local data science community.
In 2024, the data science job market in Algiers is promising, with increased demand across sectors. Industries like finance, healthcare, and telecommunications are actively recruiting data scientists.
Recognized as a leading program, the Certified Data Scientist Course in Algiers equips participants with essential skills in machine learning and data analysis.
Data science internships in Algiers are highly valuable, providing practical experience, exposure to projects, and networking opportunities, enhancing employability in the competitive job market.
Professionals in the field of Data Science in Algiers can anticipate a commendable average annual salary of DZD 74,300, according to Glassdoor reports. This figure illustrates the competitive compensation available for Data Analysts in Algiers, providing valuable insights into the earning potential within the local data science job market.
Yes, newcomers can secure data science jobs in Algiers after completing courses. Entry-level positions, such as data analysts or junior data scientists, are accessible with the right skills, portfolio, and determination. Networking locally enhances job prospects.
In Algiers, the DataMites Certified Data Scientist Course is renowned as the world's most popular and comprehensive training in Data Science and Machine Learning. It remains up-to-date with industry requirements through regular updates, providing a finely-tuned and structured learning experience for participants.
Newcomers to data science in Algiers can explore beginner-level training with options such as Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science.
Indeed, for working professionals in Algiers looking to enhance their expertise, DataMites provides specialized courses such as 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 Algiers is flexible, ranging from 1 month to 8 months based on the course level.
The Certified Data Scientist Training in Algiers is designed for beginners and intermediate learners, with no prerequisites required for enrollment.
DataMites' online data science training in Algiers facilitates adaptable, self-paced learning, accommodating various lifestyles and accessible to anyone with an internet connection. It ensures quality education, overcoming geographical constraints. The curriculum covers vital data science concepts, tailored to industry needs, with expert instructors guiding learners through the complexities for a job-aligned learning experience.
For DataMites' data science training in Algiers, the fee structure ranges from DZD 71,024 to DZD 177,581. This pricing model offers a spectrum of affordable options, allowing individuals to access quality education and advance their skills in the field of data science.
DataMites' data science training sessions are conducted by seasoned mentors and faculty members with practical expertise gained from leading companies, complemented by academic excellence from institutes such as IIMs.
Indeed, participants must bring a valid photo ID, such as a national ID card or driver's license, for the issuance of participation certificates and scheduling certification exams, if required.
DataMites ensures participants in Algiers have access to recorded sessions and supplementary materials to catch up if they miss a data science training session, facilitating flexible learning.
Yes, DataMites offers a demo class in Algiers, providing participants with an opportunity to experience the course structure and content before committing to the data science training fee.
Absolutely, DataMites in Algiers provides data science courses with internship opportunities, allowing participants to gain practical experience and apply their skills in real-world scenarios.
Tailored for managers and leaders, DataMites' "Data Science for Managers" course is designed to empower them with critical skills, ensuring a smooth integration of data science into their decision-making strategies.
Certainly, in Algiers, participants have the option to attend help sessions, fostering a better understanding of specific data science topics. This supplementary support ensures a more comprehensive and enriched learning experience.
Certainly, DataMites ensures practical learning in Algiers with its Data Scientist Course, comprising 10+ capstone projects and a live client project. This hands-on approach allows participants to hone their skills through real-world applications.
Yes, DataMites issues a Data Science Course Completion Certificate. Participants can obtain it by successfully completing the training program, fulfilling attendance requirements, and passing any associated exams or assessments.
DataMites' Flexi-Pass allows participants in data science training to attend missed sessions at a later date within the course duration, ensuring flexibility and accommodating individual schedules.
Career mentoring sessions are structured to guide participants through career development, covering resume building, interview preparation, and personalized advice, enhancing their employability and career prospects.
Diverse participant needs in Algiers are met by DataMites through a range of training methods. Live online training facilitates real-time interaction, fostering an engaging learning environment. Participants also have the option of self-paced training, accessing recorded sessions at their convenience. This approach ensures personalized learning, accommodating diverse schedules, and maximizing overall learning outcomes.
Participants completing DataMites' Data Science Training in Algiers are awarded the esteemed IABAC Certification. This internationally recognized credential signifies their command of data science concepts and practical applications, providing valuable validation and elevating their standing within the data science community.
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.