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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 an interdisciplinary field that extracts insights from data using statistical, mathematical, and programming techniques. It operates through a cyclical process involving data collection, cleaning, exploration, modeling, validation, and interpretation.
Data Science functions by iteratively applying statistical methods and machine learning algorithms to analyze data, uncover patterns, and derive meaningful insights. The process involves exploring data, building models, validating results, and continuously refining approaches.
Data Science finds applications in diverse fields, enhancing decision-making in finance, healthcare, marketing, and more. It impacts applications such as predictive analytics, customer segmentation, fraud detection, and personalized recommendations.
A Data Science pipeline includes data collection, preprocessing, feature engineering, model training, evaluation, and deployment. Key tools and programming languages like Python or R, along with machine learning libraries, are essential components.
Data Science is closely related to Big Data as it leverages advanced analytics and machine learning to extract insights from large and complex datasets. Big Data technologies provide the infrastructure to handle massive volumes of data efficiently.
In e-commerce, Data Science optimizes operations, enhances user experience, and contributes to personalized recommendation systems. It analyzes customer behavior, predicts preferences, and suggests products, leading to increased user engagement and satisfaction.
Data Science enhances cybersecurity by analyzing network traffic patterns, detecting anomalies, and identifying potential threats. Machine learning algorithms enable real-time threat detection, improving the efficiency of security measures and incident response.
Data Science is implemented across various industries, including finance for risk assessment, healthcare for diagnostics, manufacturing for process optimization, and more. It helps organizations gain insights, make data-driven decisions, and stay competitive in the rapidly evolving business landscape.
Data Science encompasses a broader scope, involving the entire data lifecycle, while machine learning is a subset focused on creating algorithms for systems to learn from data. Data Science involves data collection, cleaning, and interpretation in addition to modeling.
Certification in Data Science is open to individuals with backgrounds in mathematics, statistics, computer science, or related fields. While a degree is often preferred, some certifications may accept relevant work experience as qualification.
A strong data science portfolio involves diverse projects showcasing problem-solving skills, algorithms implemented, and meaningful insights derived. Include clear explanations of methodologies and results to demonstrate proficiency in data analysis.
Yes, individuals with non-coding backgrounds can transition to Data Science. Learn programming languages like Python, delve into data science libraries, and acquire a solid understanding of statistics and machine learning through online courses and practical projects.
While a degree in computer science, statistics, or related fields is common, diverse backgrounds like physics, engineering, or economics can qualify for a career in Data Science. Strong quantitative skills and programming proficiency are essential prerequisites.
Data Scientists require proficiency in programming languages (Python, R), statistical analysis, machine learning, and data wrangling. Strong communication skills are crucial for presenting findings to non-technical stakeholders. Critical thinking and problem-solving abilities are indispensable for extracting meaningful insights from complex datasets.
Begin by acquiring foundational skills in programming, statistics, and machine learning. Explore reputable online courses or consider local educational institutions offering data science programs. Engage with Abuja's growing tech community to network and stay updated on industry trends.
As of 2024, Abuja's data science job market is expanding, driven by increased demand in sectors like government, finance, and technology. Opportunities are arising for skilled professionals contributing to data-driven decision-making.
In Abuja, the Certified Data Scientist Course is esteemed for its comprehensive approach to data science education, covering vital topics including machine learning and data analysis.
Data science internships in Abuja provide practical experience, exposure to local industry needs, and valuable networking opportunities. Internships enhance skill sets, making candidates more competitive in the Abuja job market.
In Abuja, professionals pursuing a career in data science can expect a competitive average annual salary of NGN 1,210,000, according to Glassdoor reports. This figure provides insights into the remuneration expectations for Data Scientists in Abuja, reflecting the attractive compensation offered in the local data science job market.
Yes, it is feasible for a newcomer to undertake a data science course in Abuja and secure a job. Focus on building a strong portfolio showcasing practical projects, engage with local communities, and leverage networking opportunities to increase chances of landing entry-level positions in Abuja's evolving data science landscape.
The DataMites Certified Data Scientist Course in Abuja is acknowledged as the world's most popular and job-oriented training in Data Science and Machine Learning. Regular updates ensure alignment with industry needs, providing participants with a finely-tuned and structured learning experience tailored for effective education.
Beginner-level data science training options available in Abuja for those new to the field encompass the Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science courses.
Absolutely, working professionals in Abuja can benefit from specialized courses offered by DataMites, 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 Abuja varies, ranging from 1 month to 8 months, determined by the specific level of the course.
The Certified Data Scientist Training in Abuja is tailored for beginners and intermediate learners in data science, and no prerequisites are necessary to enroll in the course.
DataMites' online data science training in Abuja offers adaptable, self-paced learning for diverse lifestyles, accessible to anyone with an internet connection, ensuring quality education without geographical constraints. The comprehensive curriculum, addressing key data science concepts, is customized for industry needs. Expert guidance from seasoned instructors enriches learners' understanding, navigating the intricacies of data science for a job-aligned experience.
The fee structure for DataMites' data science programs in Abuja varies from NGN 474,803 to NGN 1,187,144. This diverse pricing accommodates different budgets, making quality education in data science accessible to individuals seeking skill development in Abuja.
At DataMites, data science training sessions are orchestrated by distinguished mentors and faculty members with firsthand experience in leading companies, along with qualifications from renowned institutions like IIMs.
Yes, participants need to bring a valid photo identification proof, such as a national ID card or driver's license, when obtaining participation certificates and scheduling certification exams, if required.
In the event of a missed data science training session in Abuja, participants have access to recorded sessions and supplementary materials, allowing them to catch up at their own pace.
Yes, DataMites provides an opportunity for a demo class in Abuja before committing to the data science training fee. This allows participants to explore the course structure and content firsthand.
Yes, DataMites offers data science courses with internship opportunities in Abuja, providing participants with practical, hands-on experience to reinforce their learning.
The "Data Science for Managers" course offered by DataMites is the ideal choice for managers and leaders. It focuses on equipping them with the necessary skills to integrate data science effectively into their decision-making processes.
Yes, in Abuja, there is an option for participants to attend help sessions, contributing to a more profound understanding of specific data science topics. This personalized assistance ensures participants receive comprehensive support for optimal learning outcomes.
Yes, participants in Abuja can expect hands-on experience with DataMites' Data Scientist Course, featuring 10+ capstone projects and a live client project. This practical emphasis ensures a comprehensive understanding of data science concepts through real-world projects.
Upon successful completion of the program, DataMites issues a Data Science Course Completion Certificate. This certificate is attainable by fulfilling course requirements, including assessments and projects, showcasing proficiency in data science concepts and applications.
The Flexi-Pass Concept at DataMites offers scheduling flexibility for training sessions, enabling participants to attend missed classes during other batches. This ensures they can effectively manage their learning journey and access valuable content.
DataMites' Career Mentoring Sessions provide personalized guidance on resume building, interview preparation, and career strategies. Conducted in one-on-one sessions, these mentorship opportunities aid participants in aligning their skills with industry demands, enhancing employability and career advancement.
DataMites in Abuja understands the diverse needs of participants and tailors its training methods accordingly. Live online training encourages real-time interaction, establishing an immersive learning environment. Alternatively, participants can select self-paced training, accessing recorded sessions at their convenience. This adaptable approach ensures personalized learning, accommodates diverse schedules, and maximizes overall learning outcomes.
The completion of DataMites' Data Science Training in Abuja comes with the distinguished IABAC Certification for participants. This certification, acknowledged globally, authenticates their proficiency in data science concepts and practical applications, establishing a valuable credential and bolstering their professional standing in the field of data science.
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.