Data Analytics Course By LA Bootcamps Mumbai
LA Bootcamps offers data analytics Courses that are designed to equip students with the skills they need to become successful data analysts. The course covers topics such as data visualization, data analysis, and machine learning. Students benefit from hands-on practice, and the opportunity to ask questions and receive feedback from experienced instructors. The course provides an in-depth understanding of the tools and techniques used by data analysts, and provides students with the opportunity to develop their own data analysis projects. Graduates of the course will be equipped with the knowledge and skills to pursue a successful career in data analytics. The course also prepares students for the certification exam for data analytics, allowing them to demonstrate their proficiency in the field. Additionally, graduates of the course receive a certificate of completion, which they can use to showcase their qualifications to potential employers. This certificate can be used to prove the graduate’s competency to potential employers and can help open up more job opportunities. Furthermore, graduates of the course can use the skills they have acquired to develop innovative solutions to real-world problems. The course also provides access to exclusive mentorship opportunities, allowing graduates to connect with experts in the field. This access can be invaluable in helping graduates gain valuable insight and advice.
Data Analytics Training Course Outline
Microsoft Excel for Data Analysis:
- Overview of Excel functionalities for data manipulation, analysis, and visualization.
- Formulas, functions, pivot tables, and data modeling in Excel for analytical purposes.
SQL for Data Analysis:
- Understanding Structured Query Language (SQL) and its application in retrieving and analyzing data from databases.
- Querying, filtering, and manipulating data using SQL commands.
Introduction to Data Science and Statistics:
- Basic principles of data science, statistical analysis, and probability theory.
- Introduction to key statistical concepts used in data analysis.
Presto (SQL Query Interface):
- Understanding Presto as a distributed SQL query engine for analyzing large datasets.
- Exploring its features and capabilities for efficient data querying.
Data Analysis, Project Life Cycle, and Data Science in the Real World:
- Learning methodologies and best practices in data analysis projects.
- Understanding the project life cycle in data science and its practical application in real-world scenarios.
Techniques of Evaluation, Experimentation, and Project Deployment:
- Methods and techniques for evaluating data models and experiments in a data analysis context.
- Deployment strategies for successful project implementation.
Power BI:
- Utilizing Power BI for data visualization, creating interactive dashboards, and generating insightful reports.
- Hands-on experience with Power BI functionalities.
Business Case Studies:
- Analyzing real-world business cases to understand data-driven decision-making.
- Applying analytical skills to solve business problems through case studies.
Machine Learning Techniques:
- Introduction to various machine learning algorithms and models used in data analytics.
- Understanding the application of machine learning for predictive analysis.
Data Science Capstone Project:
- Application of learned skills in a comprehensive capstone project.
- Demonstration of proficiency in data analysis, problem-solving, and project implementation.
Why become a Data Analyst
Becoming a Data Analyst can be an appealing career choice for several reasons:
1. High Demand:
Growing Industry: In today’s digital age, data is abundant, leading to an increased demand for professionals who can interpret and derive insights from this data.
Diverse Industry Opportunities: Data analysis skills are sought after in various sectors such as finance, healthcare, marketing, technology, and more.
2. Lucrative Career:
Competitive Salaries: Data Analysts often enjoy competitive salaries due to the specialized skill set and demand for their expertise.
Career Growth: Opportunities for career advancement and growth exist as the role of data analysis continues to evolve and expand.
3. Impactful Work:
Informed Decision-Making: Data Analysts play a pivotal role in aiding organizations to make informed decisions based on data-driven insights.
Problem Solving: Analyzing data allows for problem-solving and addressing challenges by identifying patterns and trends.
4. Versatile Skill Set:
Analytical Skills: Enhancing analytical skills by working with various tools, techniques, and methodologies used in data analysis.
Adaptability: Data Analysts often work with diverse datasets, which enhances their adaptability and ability to handle complex information.
5. Continuous Learning and Innovation:
Technological Advancements: Continuous learning and staying updated with technological advancements in data analysis tools and methodologies is inherent in the field.
Innovation Opportunities: The field of data analysis is dynamic, allowing for innovation and creativity in finding novel solutions to problems.
6. Job Satisfaction:
Problem Solving and Impact: Deriving insights from data and witnessing how those insights positively impact business decisions can be fulfilling.
Intellectual Challenge: Analyzing complex datasets presents intellectual challenges that keep the job engaging and rewarding.
7. Global Relevance:
Global Demand: Data analysis skills are in demand worldwide, offering opportunities for work and collaboration across borders and industries.
( FAQ ) for the Data Analytics course offered by LA Bootcamps:
1 : Is prior experience in data analytics required to enroll in this course?
- Answer: No prior experience in data analytics is required. Our course is designed to accommodate learners at various skill levels, including beginners. We provide comprehensive instruction starting from foundational concepts to advanced techniques.
2 : What kind of job placements can one expect after completing the program?
- Answer: Graduates can explore diverse career opportunities such as data analyst, business intelligence analyst, data scientist, and more. Our program equips students with the necessary skills sought after in the data analytics field, enhancing their employability.
3 : Does the course offer hands-on experience with industry tools and software?
- Answer: Yes, our curriculum includes practical training with industry-standard tools and software used in data analytics. Students gain hands-on experience, enabling them to apply their knowledge effectively in real-world scenarios.
4 : How does this program stand out from other similar data analytics courses?
- Answer: Our program stands out due to its comprehensive curriculum, dedicated faculty, emphasis on practical learning through projects, and 100% career assistance. We prioritize providing a well-rounded education with a focus on both theoretical concepts and practical applications.
5 : Can online learners access the same resources and support as on-campus students?
- Answer: Absolutely! Online learners receive access to the same resources, support, mentorship, and guidance as our on-campus students. We ensure a consistent and quality learning experience regardless of the mode of study.
Certificate & Courses
- Diploma in Cyber Security
- Post-Graduate Diploma in Cyber Security
- Certification in Cyber Security
- Post-Graduate Diploma in Data Science
- Certification in Data Analytics with Python
- Diploma in Artificial Intelligence (AI)
- Post Graduate Diploma in Artificial Intelligence (AI)
- Certification in Artificial Intelligence (AI)
- Post Graduate Diploma in Machine Learning (ML)
- Certification in Machine Learning (ML)
- Certification in Cloud Computing
- Certification in Blockchain
Tim Berners-Lee
Inventor of the World Wide Web“Data is a Precious thing and will last longer than the systems themselves”
 | Duration: 4 MONTHS Schedule: Weekdays – 2 Hrs / 4 days a week Weekends – 4 Hrs / Sat & Sun |
Unit 1: Getting started with PYTHON
Unit 2: Numerical Computing with Pandas
Unit 3: Scientific Computing with NumPy/SciPy
Unit 4: Presenting stories via simple visualizations
Unit 5: Using the NLTK (Natural Language Toolkit) Package
Unit 6: Getting insights from TWEETS
DELIVERY METHODOLOGY
- SESSIONS CONDUCTED BY TRAINER AS PER FIXED ACADEMIC CALENDAR
- PRACTICAL HANDS ON SESSIONS
- PRACTICAL SESSION ON LABS AND HANDS ON WITH EXPERTS
- ASSIGNMENTS & ASSESMENTS
- PROJECTS AND CASE STUDIES
Students who have successfully completed their course as per Terms and conditions will be eligible for the certification.
Certification in Cyber Security will be provided jointly by St. Xavier’s Technical Institute and L.A Bootcamps.
St. Xavier’s Technical Institute is affiliated to Directorate of Technical Education and approved by All India Council for Technical Education (AICTE) and autonomous institute.
ADMISSION CRITERIA
- 12th HSC or Passed and Dropouts
- BE/BTech/BSC/BCA/MTech/MSC/MCA/ or Passed out students pursuing or Graduate
- Graduate (any stream ) Studying or Passed out students
- Working professionals in the IT & Tech sector
- Any one is eligible who is excel in this program
Most data scientists start as data analysts and data engineers at the beginning of their careers. Data analysts work directly with raw data collected through the systems. This also means they work with various teams like marketing, sales, customer support, finance to process information. Data analysts clean the data, study, and create reports using data visualization tools like Tableau and Excel to help teams develop strategies.
Business Intelligence Analyst
A business intelligence analyst’s most fundamental job is to find patterns — and value — in their company and industry data. BI Analysts will be expected to be comfortable analyzing data, working with SQL, and doing data visualization and modeling.
Data Analyst
Data Analysts do exactly what the job title implies — analyze company and industry data to find value and opportunities. Unlike data scientists, they’re typically not expected to be proficient in machine learning. But most data analyst jobs require programming and SQL skills, as well as statistical knowledge, comfort with the data analysis workflow, and data visualization skills.
Marketing Analyst
Digital marketing also requires a strong knowledge of data analytics. Depending on your other complementary skills and interests, you could find yourself in a specific analytics role within a company or agency, or simply applying your data science expertise as a part of a larger skill set.
Marketers often use tools like Google Analytics, custom reporting tools and other third party sites to analyze traffic from websites and social media advertisements. While these examples require a basic understanding of data analytics, a skilled data scientist has the ability to create a long-term career in marketing.
A lot of money could be wasted on campaigns that do not drive traffic, so marketing professionals will continue to need analysts to make smart decisions about how to leverage existing resources.
Data Analytics is also important for careers like Data Scientist, Data Engineer, Quantitative Analyst, Operations Analyst, IT Systems Analyst.
L.A Bootcamps will provide 100% Placement Assistance to all students who successfully complete the course and extend below complimentary placement services to the students:
- Resume Building assistance
- Career Mentoring with Industry Professionals
- Interview Preparation sessions
- Career Fairs
- Internship opportunities for Freshers
