12+
YEARS OF
EXPERIENCE
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STUDENTS TRAINED
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100+
COMPANY
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- ABOUT
Your Dreams Deserve to be Realized, and we are here to Make It Happen
Welcome to Career Credentials, your trusted partner in career development and placement success. With a strong commitment to your professional growth, we empower individuals to unlock their full potential and secure their dream jobs with certainty. Join us at Career Credentials and unlock a world of opportunities. Ignite your potential, fuel your aspirations, and embark on a fulfilling career journey with the assurance of guaranteed job placements. Your dreams deserve to be realized, and we are here to make it happen.
- Academics
Course Curriculum
Week 1: Introduction to Data Analytics
- Introduction to Data Analytics and its applications
- Data Analytics lifecycle and process
- Data collection, cleansing, and transformation
- Introduction to Python and libraries for Data Analytics (NumPy, Pandas)
Week 2: Data Exploration and Visualization
- Exploratory Data Analysis (EDA) techniques
- Data visualization using Matplotlib and Seaborn
- Statistical analysis and summary statistics
- Data wrangling and feature engineering
Week 3: Statistical Analysis for Data Analyticsd Learning Algorithms
- Probability and Probability Distributions
- Hypothesis testing and confidence intervals
- Correlation and regression analysis
- ANOVA (Analysis of Variance)
Week 4: Data Mining Techniques
- Association Rule Mining
- Clustering techniques (K-Means, Hierarchical Clustering)
- Decision Trees and Random Forests
- Time Series Analysis and Forecasting
Week 5: Machine Learning for Data Analytics
- Supervised Learning Algorithms (Regression, Classification)
- Unsupervised Learning Algorithms (Clustering, Dimensionality Reduction)
- Model evaluation and selection
- Feature selection and extraction
Week 6: Big Data Analytics
- Introduction to Big Data and its challenges
- Apache Hadoop and HDFS
- MapReduce and Spark fundamentals
- Analyzing large datasets using Apache Spark
Week 7: Advanced Analytics Techniques
- Natural Language Processing (NLP) for text analytics
- Social Network Analysis (SNA)
- Recommender Systems
- Sentiment Analysis and Text Classification
Week 8: Data Visualization and Dashboarding
- Advanced data visualization techniques
- Interactive dashboards using Tableau or Power BI
- Storytelling with data
- Effective communication of insights and findings
- Technologies
Programming Languages & Tools
- Featured
Industry Projects
- Achievements
Our Students Get Placed In
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- Why Join Us?
Key Benefits
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- Certifications
Our Certifications
IBM Certification
The Masters in Full Stack Developer Course offers three modules: Python for Web Developers, HTML-based Web Development, and Java Fundamentals. These modules teach essential job-ready skills like Python, databases, data analysis, and more. The course are streamlined to help you easily crack the IBM certification courses. You’ll gain hands-on experience on the IBM Cloud, working with real-world tools and datasets. By the end of the course, you’ll have a portfolio of Full Stack projects, setting you up for a successful career in Full Stack Development.
AWS Certifications
In the Full Stack Development Course offered by Career Credentials, you will be equipped with the necessary skills to assist organizations in identifying and nurturing talent capable of implementing cloud initiatives. The course emphasizes the importance of becoming an AWS Certified Cloud Practitioner, as it demonstrates proficiency in cloud technologies and establishes a solid foundation of AWS knowledge. By obtaining this certification, you validate your expertise in the cloud domain and enhance your career prospects in Full Stack Development.
- Testimonials
Trusted by 90,000+ Student
Career Credentials provided a strong foundation for my full stack development career. The instructors were patient, and their industry connections led to multiple job offers before course completion.
Best career decision! Career Credentials' curriculum was comprehensive and well-paced. The instructors were experts and offered outstanding post-course support. I secured multiple job offers within a month!
- FAQ's
Frequently Asked Questions
What is Data Analytics, and why is it important?
Data Analytics is the process of examining, transforming, and modeling data to discover useful insights and support decision-making. It is important because it helps organizations uncover patterns, trends, and correlations in data to drive business strategies, optimize processes, and make data-driven decisions.
What will I learn in the Data Analytics course?
In this course, you will learn essential data analytics techniques such as data cleaning and preprocessing, exploratory data analysis, data visualization, statistical analysis, and data interpretation. You will also gain hands-on experience with popular tools and programming languages like Python and R.
Are there any prerequisites for the Data Analytics course?
The course is designed for learners with varying backgrounds, and no prior experience in data analytics is required. However, a basic understanding of statistics and familiarity with programming concepts will be beneficial.
How long does the Data Analytics course take?
The course duration is typically 8 to 12 weeks, depending on the curriculum’s depth and the pace of learning. It is designed to provide a comprehensive understanding of data analytics concepts and techniques within a reasonable timeframe.
Will I receive a certificate upon completion?
Yes, upon successful completion of the course, you will receive a certificate that validates your skills and knowledge in Data Analytics. This certificate can enhance your resume and demonstrate your proficiency in analyzing and interpreting data.
How can Data Analytics benefit my career?
Data Analytics skills are in high demand across various industries. By acquiring data analytics skills, you can pursue career opportunities as a Data Analyst, Business Analyst, Data Scientist, or Data-driven decision-maker. These roles often offer competitive salaries and provide opportunities for growth and advancement.
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