Numerous studies and reports over the years have suggested that data science is one of the fastest-growing domains, and has soared the popularity charts as the COVID-19 pandemic hit. As digital technologies are being adopted across industries, data-driven decisions are taking centre stage. Skilled data scientists have therefore become the need of the hour, and the companies are extensively hiring candidates in their data science teams. Amid the increasing competition for these job roles, data scientist candidates who have a thorough understanding of the theory along with practical exposure are an obvious choice.
The Data Science 360 course, which is a global certification program offered by AnalytixLabs (in collaboration with IBM) offers one of the best and world-class pedagogies to learn and adapt to the ever-evolving world of data science. Offering one of the most industry-relevant programs, it covers an extensive hands-on approach to help position candidates as data scientists in leading companies. The course covers nuances of data science skills from visualisation to descriptive analytics and predictive modelling, to help drive smart business decisions. This online course secured the first position in the annual ranking of top online courses conducted by Analytics India Magazine.
Customisable Course Structure For Individual Preferences
With both live and classroom classes available as per the candidates’ preference, the course enables self-paced learning while providing in-person mentorship in weekend and weekday classroom boot camps. The classroom and boot camp options are available for candidates to take up at Bangalore, Noida and Gurgaon. The sessions are also interactive, allowing students for real-time discussions and question-answer sessions.
The Data Science 360 course includes three different courses on important data science topics to provide students with a holistic picture of the domain. The course modules included as a part of this learning track are:
- Data Visualisation & Analytics (Excel, SQL & Tableau)
- Data Science With R & Python
- Machine Learning Course
The course curriculum is designed for beginners in the data science domain and covers topics beginning from the building blocks of data science and basic programming elements. Through the journey of the course, it covers topics such as data visualisation, data extraction, manipulation, analysis, reporting, building intuitive business dashboards, among others. The tools and languages that are covered during this first phase of the programme are Excel, SQL & Tableau, R.
The next phase covers core Python, NumPy and Pandas for data analysis, while also covering advanced data visualisation using in-demand Python libraries. It then covers areas such as predictive modelling, machine learning concepts, supervised and unsupervised learning, text mining, natural language processing, and more.
The highlight of the program is its intensive industrial and functional sessions that give an insight into project management, risk analysis, digital and social network analysis, and operational analysis.
Some of the skills that a candidate will acquire by the end of this course are MIS reporting analytics, data visualisation, data blending and manipulation, data mining and analysis, R programming, statistical analysis and modelling, predictive modelling, supervised machine learning, text mining and NLP, among others. The pedagogy of this program was ranked best by AIM in its data science education ranking.
Who Should Take The Course?
The course is best suited for beginner candidates who do not have a programming background but want to acquire job oriented practical skills on a prominent open-source data science platform. The candidate should be from quantitative backgrounds such as engineering, finance, math, business management and others who are looking for business analytics training to start their career in analytics and data science.
The course prepares candidates for job roles such as analytics consultant, data analyst, BI analyst, statistical analyst, among others. After completing this course, candidates can apply robust data science solutions for organisation’s data management needs that are key to business decision making.
Capstone projects: One of the major highlights of the course is that apart from multiple case studies used for class sessions, it includes extensive assignments and projects for self-study and hands-on skills.
Assignments: It includes three analytics case studies that test the skills in R. Apart from this, the assignments provide a hands-on Excel, SQL, Tableau, NumPy, Pandas, Python, visual analytics, statistical analysis and more.
Projects: Candidates get to solve numerous projects which are industry-relevant and lets the candidate have hands-on experience on various mechanisms such as recommendation engine, predictive analytics, churn prediction, marketing & sales data manipulation & analysis, across industries such as retail, telecom, sports, consumer electronics, and more.
Career support in terms of:
- Profile building where a team of seasoned professionals provide personalised help for preparing CV and online profiles.
- Interview preparation where candidates are prepared for one to one interviews apart from guiding career development tasks
- Job referrals where candidates are provided referrals from various organisations, clients, HR consultants and a large pool of AnalytixLabs’ alumni working in various companies.
- Continuous support as long as a candidate needs it.
Once the program is complete, the evaluation of candidates is done based on MCQs, assignment and projects done during the program. On successful completion of the course, the candidate is given a certificate which is highly regarded in the industry. The course is also ranked best in parameters such as graduation outcome, ROI and brand value. It also has good student reviews and gender diversity ratio.
The course even claims a job guarantee or money back program, which is a win-win situation for the candidates. The institute states that they will refund 100% of paid tuition fee, excluding taxes, if a candidate is not offered the Qualifying Position within six months of receiving the certificate of completion, subjected to the stipulated requirements and terms.
Total no of hours: 138 hrs + 74 hrs e-learning
Self Study Hours: 260 (8-10 hrs/week)
Assignments & Projects: 18
Course Fees: Starting from ₹42000
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Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.